Comparing charities - planned data analysis code
Setup and data loading
Loading packages (don’t touch this)
# Knit function options
knitr::opts_chunk$set(echo = TRUE, clean = TRUE)
# Downloading and installing required packages
list.of.packages <- c("tidyverse", "haven", "jmv", "ggstatsplot", "DataExplorer", "reshape2", "labelled", "grateful", "rstudioapi")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages, dependencies = TRUE)
invisible(lapply(list.of.packages, library, character.only = TRUE))## Warning: package 'tidyverse' was built under R version 4.2.3## Warning: package 'ggplot2' was built under R version 4.2.3## Warning: package 'tibble' was built under R version 4.2.3## Warning: package 'tidyr' was built under R version 4.2.3## Warning: package 'readr' was built under R version 4.2.3## Warning: package 'purrr' was built under R version 4.2.3## Warning: package 'dplyr' was built under R version 4.2.3## Warning: package 'stringr' was built under R version 4.2.2## Warning: package 'forcats' was built under R version 4.2.3## Warning: package 'lubridate' was built under R version 4.2.3## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the ]8;;http://conflicted.r-lib.org/conflicted package]8;; to force all conflicts to become errors## Warning: package 'haven' was built under R version 4.2.3## Warning: package 'ggstatsplot' was built under R version 4.2.3## You can cite this package as:
## Patil, I. (2021). Visualizations with statistical details: The 'ggstatsplot' approach.
## Journal of Open Source Software, 6(61), 3167, doi:10.21105/joss.03167## Warning: package 'DataExplorer' was built under R version 4.2.3##
## Attaching package: 'reshape2'
##
## The following object is masked from 'package:tidyr':
##
## smiths## Warning: package 'labelled' was built under R version 4.2.3## Warning: package 'grateful' was built under R version 4.2.3## Warning: package 'rstudioapi' was built under R version 4.2.3# Miscellaneous settings
Sys.setenv(LANG = "en")
options(scipen=999.99)
options(es.use_symbols = TRUE)
AnalyzeComparison <- function (dataset, VarName, Title, AgainstValue) {
set.seed(513131)
internaldataset <- data.frame(dataset[[VarName]])
# print (paste ("Descriptives of", Title))
# print ("========================")
#
# print(jmv::descriptives(
# data = internaldataset,
# vars = vars(dataset..VarName..),
# hist = TRUE,
# dens = TRUE,
# box = TRUE,
# violin = TRUE,
# dot = TRUE,
# boxMean = TRUE,
# ci = TRUE))
# print (paste("One sample t-test against",AgainstValue))
# print ("=============================")
print(jmv::ttestOneS(
data = internaldataset,
vars = vars(dataset..VarName..),
testValue = AgainstValue,
meanDiff = TRUE,
effectSize = TRUE,
ciES = TRUE,
desc = TRUE,
plots = FALSE))
# print ("Plot")
# print ("============")
internaldataset$dataset..VarName.. <- as.numeric(internaldataset$dataset..VarName..)
gghistostats(
data = internaldataset,
x = dataset..VarName..,
xlab = "% allocation to B",
bf.message = TRUE,
binwidth = 10,
title = Title,
test.value = AgainstValue,
point.args = list(size = 2, alpha = 0.2,
position = ggplot2::position_jitterdodge(
jitter.width = 0.3,
jitter.height = 0.3))
)
}Overview of dataset
## [1] "StartDate" "EndDate"
## [3] "Status" "Progress"
## [5] "Duration__in_seconds_" "Finished"
## [7] "RecordedDate" "ResponseId"
## [9] "RecipientLastName" "RecipientFirstName"
## [11] "RecipientEmail" "ExternalReference"
## [13] "DistributionChannel" "UserLanguage"
## [15] "Q_RecaptchaScore" "Q_RelevantIDDuplicate"
## [17] "Q_RelevantIDDuplicateScore" "Q_RelevantIDFraudScore"
## [19] "Q_RelevantIDLastStartDate" "consentagree_1"
## [21] "outline1" "outline1_DO_1"
## [23] "outline1_DO_0" "outline1_DO_99"
## [25] "outline2" "outline2_DO_1"
## [27] "outline2_DO_0" "outline2_DO_99"
## [29] "native" "native_DO_1"
## [31] "native_DO_0" "native_DO_2"
## [33] "copy_paste" "A1_1allocation"
## [35] "A1_1thoughts" "A2_1allocation"
## [37] "A2_1thoughts" "A3_1allocation"
## [39] "A3_1thoughts" "A4_1allocation"
## [41] "A4_1thoughts" "A5_1allocation"
## [43] "A5_1thoughts" "A7_1allocation"
## [45] "A7_1thoughts" "A8_1allocation"
## [47] "A8_1thoughts" "A9_1allocation"
## [49] "A9_1thoughts" "A10_1allocation"
## [51] "A10_1thoughts" "A11_1allocation"
## [53] "A11_1thoughts" "A12_1allocation"
## [55] "A12_1thoughts" "A13_1allocation"
## [57] "A13_1thoughts" "A14_1allocation"
## [59] "A14_1thoughts" "A15_1allocation"
## [61] "A15_1thoughts" "A16_1allocation"
## [63] "A16_1thoughts" "A17_1allocation"
## [65] "A17_1thoughts" "A18_1allocation"
## [67] "A18_1thoughts" "A19_1allocation"
## [69] "A19_1thoughts" "A20_1allocation"
## [71] "A20_1thoughts" "A21_1allocation"
## [73] "A21_1thoughts" "A22_1allocation"
## [75] "A22_1thoughts" "A23_1allocation"
## [77] "A23_1thoughts" "A24_1allocation"
## [79] "A24_1thoughts" "A1_2allocation"
## [81] "A1_2thoughts" "A2_2allocation"
## [83] "A2_2thoughts" "A3_2allocation"
## [85] "A3_2thoughts" "A4_2allocation"
## [87] "A4_2thoughts" "A5_2allocation"
## [89] "A5_2thoughts" "A6_2allocation"
## [91] "A6_2thoughts" "A7_2allocation"
## [93] "A7_2thoughts" "A8_2allocation"
## [95] "A8_2thoughts" "A9_2allocation"
## [97] "A9_2thoughts" "A10_2allocation"
## [99] "A10_2thoughts" "A11_2allocation"
## [101] "A11_2thoughts" "A12_2allocation"
## [103] "A12_2thoughts" "A13_2allocation"
## [105] "A13_2thoughts" "A14_2allocation"
## [107] "A14_2thoughts" "A15_2allocation"
## [109] "A15_2thoughts" "A16_2allocation"
## [111] "A16_2thoughts" "A17_2allocation"
## [113] "A17_2thoughts" "A18_2allocation"
## [115] "A18_2thoughts" "A19_2allocation"
## [117] "A19_2thoughts" "A20_2allocation"
## [119] "A20_2thoughts" "A21_2allocation"
## [121] "A21_2thoughts" "A22_2allocation"
## [123] "A22_2thoughts" "A23_2allocation"
## [125] "A23_2thoughts" "A24_2allocation"
## [127] "A24_2thoughts" "A25_2allocation"
## [129] "A25_2thoughts" "A26_2allocation"
## [131] "A26_2thoughts" "A27_2allocation"
## [133] "A27_2thoughts" "A28_2allocation"
## [135] "A28_2thoughts" "A29_2allocation"
## [137] "A29_2thoughts" "A30_2allocation"
## [139] "A30_2thoughts" "A31_2allocation"
## [141] "A31_2thoughts" "A32_2allocation"
## [143] "A32_2thoughts" "A33_2allocation"
## [145] "A33_2thoughts" "A34_2allocation"
## [147] "A34_2thoughts" "A35_2allocation"
## [149] "A35_2thoughts" "A36_2allocation"
## [151] "A36_2thoughts" "A37_2allocation"
## [153] "A37_2thoughts" "A38_2allocation"
## [155] "A38_2thoughts" "A39_2allocation"
## [157] "A39_2thoughts" "A40_2allocation"
## [159] "A40_2thoughts" "A41_2allocation"
## [161] "A41_2thoughts" "A42_2allocation"
## [163] "A42_2thoughts" "A43_2allocation"
## [165] "A43_2thoughts" "A44_2allocation"
## [167] "A44_2thoughts" "A45_2allocation"
## [169] "A45_2thoughts" "A46_2allocation"
## [171] "A46_2thoughts" "A47_2allocation"
## [173] "A47_2thoughts" "A48_2allocation"
## [175] "A48_2thoughts" "A49_2allocation"
## [177] "A49_2thoughts" "A50_2allocation"
## [179] "A50_2thoughts" "A51_2allocation"
## [181] "A51_2thoughts" "A52_2allocation"
## [183] "A52_2thoughts" "A53_2allocation"
## [185] "A53_2thoughts" "A54_2allocation"
## [187] "A54_2thoughts" "A55_2allocation"
## [189] "A55_2thoughts" "A56_2allocation"
## [191] "A56_2thoughts" "A57_2allocation"
## [193] "A57_2thoughts" "A58_2allocation"
## [195] "A58_2thoughts" "A59_2allocation"
## [197] "A59_2thoughts" "A60_2allocation"
## [199] "A60_2thoughts" "A61_2allocation"
## [201] "A61_2thoughts" "A62_2allocation"
## [203] "A62_2thoughts" "A63_2allocation"
## [205] "A63_2thoughts" "A64_2allocation"
## [207] "A64_2thoughts" "A65_2allocation"
## [209] "A65_2thoughts" "A66_2allocation"
## [211] "A66_2thoughts" "A67_2allocation"
## [213] "A67_2thoughts" "A68_2allocation"
## [215] "A68_2thoughts" "A69_2allocation"
## [217] "A69_2thoughts" "A70_2allocation"
## [219] "A70_2thoughts" "A71_2allocation"
## [221] "A71_2thoughts" "A72_2allocation"
## [223] "A72_2thoughts" "A73_2allocation"
## [225] "A73_2thoughts" "A74_2allocation"
## [227] "A74_2thoughts" "A75_2allocation"
## [229] "A75_2thoughts" "A76_2allocation"
## [231] "A76_2thoughts" "A77_2allocation"
## [233] "A77_2thoughts" "A78_2allocation"
## [235] "A78_2thoughts" "A79_2allocation"
## [237] "A79_2thoughts" "A80_2allocation"
## [239] "A80_2thoughts" "A81_2allocation"
## [241] "A81_2thoughts" "serious"
## [243] "seen" "seen_1_TEXT"
## [245] "funnel_purpose" "funnel_improve"
## [247] "age" "gender"
## [249] "origin" "residence"
## [251] "soc_class" "understanding"
## [253] "politicalcat" "politicalcat_4_TEXT"
## [255] "politicialcont" "funnel_pay"
## [257] "assignmentId" "hitId"
## [259] "CountryCode" "CountryName"
## [261] "STUDY_ID" "SESSION_ID"
## [263] "PROLIFIC_PID" "Q_BallotBoxStuffing"
## [265] "Q_TotalDuration" "RandomID"
## [267] "Block"
Analyses: Connected scenarios with within-subject effects
Pre-registration general criteria: Alpha (p-values) = .001
Framing (H1)
Framing positive (A: Risk averse, B: Risk seeking) (H1a)
Charities A and B both save lives of those facing likely death. Donation to Charity A means a 100% certainty that 50 lives are saved for every 100 people facing likely death. Donation to Charity B means that out of 100 people facing likely death, there is a 50% chance of saving all 100 people, and a 50% chance of not saving any lives at all (0 out of 100).
H1a: In positive framing, people show a tendency towards risk aversion (<50).
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -11.19965 114.0000 < .0000001 -24.52174 Cohen's d -1.044373 -1.270322 -0.8153955
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 25.47826 20.00000 23.47987 2.189509
## ─────────────────────────────────────────────────────────────────────────────
Framing negative (A: Risk averse, B: Risk seeking) (H1b)
Charities A and B both prevent lives lost of those facing likely death. Donation to Charity A means a 100% certainty that 50 lives are lost for every 100 people facing likely death. Donation to Charity B means that out of 100 people facing likely death, there is a 50% chance of no lives (0 out of 100) lost at all, and a 50% chance of losing all 100 people.
H1b: In negative framing, people show a tendency towards risk seeking (>50).
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -4.419079 114.0000 0.0000227 -11.47826 Cohen's d -0.4120812 -0.6016635 -0.2208288
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 38.52174 50.00000 27.85437 2.597433
## ─────────────────────────────────────────────────────────────────────────────
Framing positive vs. negative (H1a+b)
H1a+b: Those in negative framing show a stronger tendency towards risk seeking than those in positive framing.
jmv::anovaRM(
data = data,
rm = list(
list(
label="Framing",
levels=c(
"Positive framing",
"Negative framing"))),
rmCells = list(
list(
measure="A1_1allocation",
cell="Positive framing"),
list(
measure="A2_1allocation",
cell="Negative framing")),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ Framing,
postHoc = list(
"Framing"),
emMeans = ~ Framing,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Framing 9782.609 1 9782.6087 21.60546 0.0000091 0.0607314 0.1593259
## Residual 51617.391 114 452.7841
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 99680.00 114 874.3860
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - Framing
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Framing Framing Mean Difference SE df t p-tukey
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Positive framing - Negative framing -13.04348 2.806155 114.0000 -4.648167 0.0000091
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## FRAMING
##
## Estimated Marginal Means - Framing
## ────────────────────────────────────────────────────────────────────
## Framing Mean SE Lower Upper
## ────────────────────────────────────────────────────────────────────
## Positive framing 25.47826 2.189509 21.14086 29.81566
## Negative framing 38.52174 2.597433 33.37624 43.66723
## ────────────────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_framing <- data.frame(data$A1_1allocation,
data$A2_1allocation)
colnames(data_framing) <- c("Positive framing", "Negative framing")
data_framing_mod <- melt(data_framing)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_framing_mod <- data.frame(data_framing_mod)
data_framing_mod <- na.omit(data_framing_mod)
data_framing_mod <- remove_labels(data_framing_mod)
ggwithinstats(
data = data_framing_mod,
x = variable,
y = value,
xlab = "Framing",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Framing: positive vs. negative",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
Effort (H2)
Picnic (H2a)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Imagine that a donation of $1,000 or more to Charity A requires that you attend their events with relaxed and enjoyable picnic for fundraising where attendees can enjoy food, games, and music. A donation to Charity B does not require you to attend any events. You have $2,000 to allocate between the two charities.
H2a: People prefer donations without additional obligations over donations attending relaxing events.
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 6.561382 114.0000 < .0000001 18.78261 Cohen's d 0.6118521 0.4114706 0.8099565
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 68.78261 60.00000 30.69796 2.862599
## ─────────────────────────────────────────────────────────────────────────────
10 mile (H2b)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Imagine that a donation of $1,000 or more to Charity A requires that you attend their challenging 10 mile (16 kilometers) charity run. A donation to Charity B does not require you to attend any events. You have $2,000 to allocate between the two charities.
H2b: People prefer donations without additional obligations over donations attending highly effortful events.
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 10.55408 114.0000 < .0000001 29.73913 Cohen's d 0.9841735 0.7597888 1.205593
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 79.73913 100.0000 30.21737 2.817784
## ─────────────────────────────────────────────────────────────────────────────
1 mile (H2c)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Imagine that a donation of $1,000 or more to Charity A requires that you attend their symbolic 1 mile (1.6 kilometers) charity run. A donation to Charity B does not require you to attend any events. You have $2,000 to allocate between the two charities.
H2c: People prefer donations without additional obligations over donations attending mildly effortful events.
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 9.666723 114.0000 < .0000001 26.43478 Cohen's d 0.9014266 0.6830574 1.116940
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 76.43478 100.0000 29.32550 2.734617
## ─────────────────────────────────────────────────────────────────────────────
Compare all Effort conditions (H2a+b+c)
H2a+b+c (common sense): Preferences will be H2a (relaxing) >=~ H2c (mild effortful) >=~ H2b (highly effortful). H2a+b+c (Alternative: Martyrdom-Effect): Preferences will be H2a (relaxing) ~=< H2c (mild effortful) ~=< H2b (highly effortful).
jmv::anovaRM(
data = data,
rm = list(
list(
label="Effort",
levels=c("Picnic", "10 mile", "1 mile"))),
rmCells = list(
list(
measure="A3_1allocation",
cell="Picnic"),
list(
measure="A4_1allocation",
cell="10 mile"),
list(
measure="A5_1allocation",
cell="1 mile")),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ Effort,
postHoc = list(
"Effort"),
emMeans = ~ Effort,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Effort 7264.928 2 3632.4638 7.827865 0.0005153 0.0229304 0.0642535
## Residual 105801.739 228 464.0427
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 203758.3 114 1787.353
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - Effort
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Effort Effort Mean Difference SE df t p-tukey
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Picnic - 10 mile -10.956522 3.177855 114.0000 -3.447773 0.0022709
## - 1 mile -7.652174 2.941926 114.0000 -2.601077 0.0281764
## 10 mile - 1 mile 3.304348 2.336073 114.0000 1.414489 0.3368568
## ────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## EFFORT
##
## Estimated Marginal Means - Effort
## ───────────────────────────────────────────────────────────
## Effort Mean SE Lower Upper
## ───────────────────────────────────────────────────────────
## Picnic 68.78261 2.862599 63.11182 74.45340
## 10 mile 79.73913 2.817784 74.15712 85.32114
## 1 mile 76.43478 2.734617 71.01753 81.85204
## ───────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_effort <- data.frame(data$A3_1allocation,
data$A4_1allocation,
data$A5_1allocation)
colnames(data_effort) <- c("Picnic", "10 mile", "1 mile")
data_effort_mod <- melt(data_effort)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_effort_mod <- data.frame(data_effort_mod)
data_effort_mod <- na.omit(data_effort_mod)
data_effort_mod <- remove_labels(data_effort_mod)
ggwithinstats(
data = data_effort_mod,
x = variable,
y = value,
xlab = "Effort",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Effort: Picnic vs. 10 mile vs. 1 mile",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
Target: All children, orphan children, and animals (H3)
All children vs. orphans (H3a)
Charities A and B are both charities that provide food, shelter, and medication. Charity A aims to provide that aid to all children in need, regardless of their background. Charity B aims to provide that aid to orphan children in need.
H3a: People prefer to donate to orphans over donating to all children.
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -3.283144 114.0000 0.0013634 -8.000000 Cohen's d -0.3061547 -0.4925415 -0.1184848
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 42.00000 50.00000 26.13058 2.436689
## ─────────────────────────────────────────────────────────────────────────────
Children vs. animals (H3b)
Charities A and B are both charities that provide food, shelter, and medication. Charity A aims to provide that aid to children in need. Charity B aims to provide that aid to animals in need.
H3b: Children > animals (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -9.348769 114.0000 < .0000001 -22.69565 Cohen's d -0.8717772 -1.085267 -0.6554767
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 27.30435 20.00000 26.03377 2.427662
## ─────────────────────────────────────────────────────────────────────────────
Target: Comparing all conditions (H3a+b)
H3a+b: Effect for H3b >=~ H3a.
jmv::anovaRM(
data = data,
rm = list(
list(
label="Target",
levels=c(
"All children vs. orphans",
"Children vs. animals"))),
rmCells = list(
list(
measure="A7_1allocation",
cell="All children vs. orphans"),
list(
measure="A8_1allocation",
cell="Children vs. animals")),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ Target,
postHoc = list(
"Target"),
emMeans = ~ Target,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Target 12417.83 1 12417.8261 20.38871 0.0000155 0.0741265 0.1517144
## Residual 69432.17 114 609.0542
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 85672.17 114 751.5103
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - Target
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Target Target Mean Difference SE df t p-tukey
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## All children vs. orphans - Children vs. animals 14.69565 3.254573 114.0000 4.515385 0.0000155
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## TARGET
##
## Estimated Marginal Means - Target
## ────────────────────────────────────────────────────────────────────────────
## Target Mean SE Lower Upper
## ────────────────────────────────────────────────────────────────────────────
## All children vs. orphans 42.00000 2.436689 37.17294 46.82706
## Children vs. animals 27.30435 2.427662 22.49517 32.11353
## ────────────────────────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_childrenanimals <- data.frame(data$A7_1allocation,
data$A8_1allocation)
colnames(data_childrenanimals) <- c("Children: all versus orphan", "Children versus animals")
data_childrenanimals_mod <- melt(data_childrenanimals)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_childrenanimals_mod <- data.frame(data_childrenanimals_mod)
data_childrenanimals_mod <- na.omit(data_childrenanimals_mod)
data_childrenanimals_mod <- remove_labels(data_childrenanimals_mod)
ggwithinstats(
data = data_childrenanimals_mod,
x = variable,
y = value,
xlab = "Target",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Target: Comparing conditions",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
Singularity: number of victims and gender (H4)
1 boy versus 2 children (H4a)
Charity A is seeking donations to support Jeremiah, a little boy, facing the threat of starvation, and donations are used to directly support him for him to achieve adequate living standards. Charity B is seeking donations for Tanaya and Eliah, two little children, a girl and a boy. The two of them are facing the threat of starvation, and donations are used to directly support them for them to achieve adequate living standards.
H4a (IVE): People donate more to the 1 boy compared to 2 children (<50) H4a (IVE reframed): People donate the same to the 1 boy compared to 2 children (~50 null) H4a (IVE equal): People donate the same to all 3 children (~66.6, null)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 8.831203 114.0000 < .0000001 14.52174 Cohen's d 0.8235139 0.6104784 1.033818
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 64.52174 70.00000 17.63387 1.644367
## ─────────────────────────────────────────────────────────────────────────────
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -0.8989847 114.0000 0.3705557 -1.478261 Cohen's d -0.08383075 -0.2667382 0.09944275
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 66
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 64.52174 70.00000 17.63387 1.644367
## ─────────────────────────────────────────────────────────────────────────────
1 girl versus 2 children
Charity A is seeking donations to support Rokia, a little girl, facing the threat of starvation, and donations are used to directly support her for her to achieve adequate living standards. Charity B is seeking donations for Tanaya and Eliah, two little children, a girl and a boy. The two of them are facing the threat of starvation, and donations are used to directly support them for them to achieve adequate living standards.
H4a (IVE): People donate more to the 1 boy compared to 2 children (<50) H4a (IVE reframed): People donate the same to the 1 boy compared to 2 children (~50 null) H4a (IVE equal): People donate the same to all 3 children (~66.6, null)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 8.226799 114.0000 < .0000001 14.52174 Cohen's d 0.7671530 0.5577562 0.9739188
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 64.52174 60.00000 18.92939 1.765175
## ─────────────────────────────────────────────────────────────────────────────
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -0.8374586 114.0000 0.4040871 -1.478261 Cohen's d -0.07809341 -0.2609722 0.1051244
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 66
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 64.52174 60.00000 18.92939 1.765175
## ─────────────────────────────────────────────────────────────────────────────
1 boy versus 3 children (H4b)
Charity A is seeking donations to support Jeremiah, a little boy, facing the threat of starvation, and donations are used to directly support him for him to achieve adequate living standards. Charity B is seeking donations for Tanaya, Eliah, and Mika, three little children, two girls and a boy. The three of them are facing the threat of starvation, and donations are used to directly support them for them to achieve adequate living standards.
H4b (IVE): People donate more to the 1 boy compared to 3 children (<50) H4b (IVE reframed): People donate the same to the 1 boy compared to 3 children (~50 null) H4b (IVE equal): People donate the same to all 4 children (~75, null)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 11.35297 114.0000 < .0000001 20.17391 Cohen's d 1.058670 0.8285776 1.285718
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 70.17391 70.00000 19.05590 1.776972
## ─────────────────────────────────────────────────────────────────────────────
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -2.715905 114.0000 0.0076390 -4.826087 Cohen's d -0.2532594 -0.4384150 -0.06702774
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 75
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 70.17391 70.00000 19.05590 1.776972
## ─────────────────────────────────────────────────────────────────────────────
1 girl versus 3 children
Charity A is seeking donations to support Rokia, a little girl, facing the threat of starvation, and donations are used to directly support her for her to achieve adequate living standards. Charity B is seeking donations for Tanaya, Eliah, and Mika, three little children, two girls and a boy. The three of them are facing the threat of starvation, and donations are used to directly support them for them to achieve adequate living standards.
H4b (IVE): People donate more to the 1 boy compared to 3 children (<50) H4b (IVE reframed): People donate the same to the 1 boy compared to 3 children (~50 null) H4b (IVE equal): People donate the same to all 4 children (~75, null)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 10.48236 114.0000 < .0000001 18.95652 Cohen's d 0.9774850 0.7535954 1.198416
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 68.95652 70.00000 19.39316 1.808421
## ─────────────────────────────────────────────────────────────────────────────
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -3.341853 114.0000 0.0011260 -6.043478 Cohen's d -0.3116294 -0.4981576 -0.1237973
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 75
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 68.95652 70.00000 19.39316 1.808421
## ─────────────────────────────────────────────────────────────────────────────
Compare all IVE conditions
Combined predictions
H4a+b (IVE): 1 child > 2 children > 3 children H4a+b (Scope insensitivity): 1 child ~= 2 children ~= 3 children (null)
jmv::anovaRM(
data = data,
rm = list(
list(
label="1-2 vs. 1-3",
levels=c("1 vs. 2", "1 vs. 3")),
list(
label="1 child gender",
levels=c("Boy", "Girl"))),
rmCells = list(
list(
measure="A9_1allocation",
cell=c("1 vs. 2", "Boy")),
list(
measure="A10_1allocation",
cell=c("1 vs. 2", "Girl")),
list(
measure="A11_1allocation",
cell=c("1 vs. 3", "Boy")),
list(
measure="A12_1allocation",
cell=c("1 vs. 3", "Girl"))),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ `1 child gender` + `1-2 vs. 1-3` + `1 child gender`:`1-2 vs. 1-3`,
postHoc = list(
"1 child gender",
"1-2 vs. 1-3"),
emMeans = ~ `1 child gender`:`1-2 vs. 1-3`,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## 1 child gender 42.60870 1 42.60870 0.4202844 0.5180988 0.0002605 0.0036732
## Residual 11557.39130 114 101.38063
## 1-2 vs. 1-3 2925.21739 1 2925.21739 26.1041454 0.0000013 0.0178826 0.1863196
## Residual 12774.78261 114 112.05950
## 1 child gender:1-2 vs. 1-3 42.60870 1 42.60870 0.7640542 0.3839004 0.0002605 0.0066576
## Residual 6357.39130 114 55.76659
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 129879.1 114 1139.291
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - 1 child gender
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────
## 1 child gender 1 child gender Mean Difference SE df t p-tukey
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Boy - Girl 0.6086957 0.9389199 114.0000 0.6482935 0.5180988
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## Post Hoc Comparisons - 1-2 vs. 1-3
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## 1-2 vs. 1-3 1-2 vs. 1-3 Mean Difference SE df t p-tukey
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## 1 vs. 2 - 1 vs. 3 -5.043478 0.9871324 114.0000 -5.109222 0.0000013
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## 1 CHILD GENDER:1-2 VS. 1-3
##
## Estimated Marginal Means - 1 child gender:1-2 vs. 1-3
## ─────────────────────────────────────────────────────────────────────────────────
## 1-2 vs. 1-3 1 child gender Mean SE Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────
## 1 vs. 2 Boy 64.52174 1.644367 61.26426 67.77922
## Girl 64.52174 1.765175 61.02494 68.01854
## 1 vs. 3 Boy 70.17391 1.776972 66.65375 73.69408
## Girl 68.95652 1.808421 65.37405 72.53899
## ─────────────────────────────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_IVE <- data.frame(data$A9_1allocation,
data$A10_1allocation,
data$A11_1allocation,
data$A12_1allocation)
colnames(data_IVE) <- c("1 boy versus 2 children",
"1 girl versus 2 children",
"1 boy versus 3 children",
"1 girl versus 3 children")
data_IVE_mod <- melt(data_IVE)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_IVE_mod <- data.frame(data_IVE_mod)
data_IVE_mod <- na.omit(data_IVE_mod)
data_IVE_mod <- remove_labels(data_IVE_mod)
ggwithinstats(
data = data_IVE_mod,
x = variable,
y = value,
xlab = "IVE",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Compare all IVE conditions",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
Children vs. animals vs. trees (H5)
10 animals 1 child (H5a1)
Charities A and B are charities operating in the Amazon rain-forest. Charity A focuses on helping endangered animals and can save 10 endangered animals for every $2,000 donated. Charity B focuses on helping children at risk and can save 1 child for every $2,000 donated. Imagine that you have $20,000 to allocate between the two charities.
H5a1: People prefer 1 child over 10 animals (>50)
(Note: The pre-registration had an oversight and wrote “<50” yet Charity B is the one with the 1 child, so correted to “>50”)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 6.047613 114.0000 < .0000001 17.39130 Cohen's d 0.5639429 0.3660186 0.7597194
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 67.39130 70.00000 30.83877 2.875730
## ─────────────────────────────────────────────────────────────────────────────
10 animals 10 children (H5a2)
Charities A and B are charities operating in the Amazon rain-forest. Charity A focuses on helping endangered animals and can save 10 endangered animals for every $2,000 donated. Charity B focuses on helping children at risk and can save 10 children for every $2,000 donated. Imagine that you have $20,000 to allocate between the two charities.
H5a2: People prefer 10 children over 10 animals (>50)
(Note a deviation: In the pre-registration there was an oversight written “<50” but given that Charity B is the one with children is should be “>50”. )
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 9.355908 114.0000 < .0000001 22.52174 Cohen's d 0.8724429 0.6560971 1.085977
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 72.52174 80.00000 25.81457 2.407221
## ─────────────────────────────────────────────────────────────────────────────
100 animals 1 child (H5a3)
Charities A and B are charities operating in the Amazon rain-forest. Charity A focuses on helping endangered animals and can save 100 endangered animals for every $2,000 donated. Charity B focuses on helping children at risk and can save 1 child for every $2,000 donated. Imagine that you have $20,000 to allocate between the two charities.
H5a3: People prefer 1 child over 100 animals (>50)
(Note a deviation: In the pre-registration there was an oversight written “<50” but given that Charity B is the one with children is should be “>50”. )
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 3.812892 114.0000 0.0002233 11.91304 Cohen's d 0.3555540 0.1663254 0.5433112
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 61.91304 70.00000 33.50558 3.124412
## ─────────────────────────────────────────────────────────────────────────────
1 animal 10 trees (H5b1)
Charities A and B are charities operating in the Amazon rain-forest. Charity A focuses on helping endangered animals and can save 1 endangered animal for every $2,000 donated. Charity B focuses on saving endangered trees from being cut down and can save 10 endangered trees for every $2,000 donated. Imagine that you have $20,000 to allocate between the two charities.
H5b1: People prefer 1 animal over 10 trees
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -0.4015364 114.0000 0.6887770 -0.9565217 Cohen's d -0.03744346 -0.2201937 0.1454734
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 49.04348 50.00000 25.54576 2.382154
## ─────────────────────────────────────────────────────────────────────────────
1 animal 1000 trees (H5b2)
Charities A and B are charities operating in the Amazon rain-forest. Charity A focuses on helping endangered animals and can save 1 endangered animal for every $2,000 donated. Charity B focuses on saving endangered trees from being cut down and can save 1,000 endangered trees for every $2,000 donated. Imagine that you have $20,000 to allocate between the two charities.
H5b2: People prefer 1 animal over 1000 trees
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.317340 114.0000 0.0222703 6.782609 Cohen's d 0.2160931 0.03072732 0.4005333
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 56.78261 50.00000 31.38744 2.926894
## ─────────────────────────────────────────────────────────────────────────────
Comparing all conditions
H5a+b: children > animals > trees
jmv::anovaRM(
data = data,
rm = list(
list(
label="Target",
levels=c(
"10 animals 1 child",
"10 animals 10 children",
"100 animals 1 child",
"1 animal 10 trees",
"1 animal 1000 trees"))),
rmCells = list(
list(
measure="A13_1allocation",
cell="10 animals 1 child"),
list(
measure="A14_1allocation",
cell="10 animals 10 children"),
list(
measure="A15_1allocation",
cell="100 animals 1 child"),
list(
measure="A16_1allocation",
cell="1 animal 10 trees"),
list(
measure="A17_1allocation",
cell="1 animal 1000 trees")),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ Target,
postHoc = list(
"Target"),
emMeans = ~ Target,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────────────
## Target 38383.65 4 9595.9130 15.98522 < .0000001 0.0714177 0.1229772
## Residual 273736.35 456 600.2990
## ────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 225333.2 114 1976.607
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - Target
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Target Target Mean Difference SE df t p-tukey
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## 10 animals 1 child - 10 animals 10 children -5.130435 2.079155 114.0000 -2.467557 0.1054105
## - 100 animals 1 child 5.478261 2.104238 114.0000 2.603441 0.0764497
## - 1 animal 10 trees 18.347826 3.792744 114.0000 4.837613 0.0000404
## - 1 animal 1000 trees 10.608696 3.981818 114.0000 2.664285 0.0657985
## 10 animals 10 children - 100 animals 1 child 10.608696 2.248101 114.0000 4.718959 0.0000658
## - 1 animal 10 trees 23.478261 3.117441 114.0000 7.531262 < .0000001
## - 1 animal 1000 trees 15.739130 3.293571 114.0000 4.778743 0.0000515
## 100 animals 1 child - 1 animal 10 trees 12.869565 3.959685 114.0000 3.250149 0.0129231
## - 1 animal 1000 trees 5.130435 4.288180 114.0000 1.196413 0.7534328
## 1 animal 10 trees - 1 animal 1000 trees -7.739130 2.392018 114.0000 -3.235397 0.0135154
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## TARGET
##
## Estimated Marginal Means - Target
## ──────────────────────────────────────────────────────────────────────────
## Target Mean SE Lower Upper
## ──────────────────────────────────────────────────────────────────────────
## 10 animals 1 child 67.39130 2.875730 61.69451 73.08810
## 10 animals 10 children 72.52174 2.407221 67.75305 77.29043
## 100 animals 1 child 61.91304 3.124412 55.72361 68.10248
## 1 animal 10 trees 49.04348 2.382154 44.32445 53.76251
## 1 animal 1000 trees 56.78261 2.926894 50.98445 62.58076
## ──────────────────────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_type <- data.frame(data$A13_1allocation,
data$A14_1allocation,
data$A15_1allocation,
data$A16_1allocation,
data$A17_1allocation)
colnames(data_type) <- c("10 animals 1 child",
"10 animals 10 children",
"100 animals 1 child",
"1 animal 10 trees",
"1 animal 1000 trees")
data_type_mod <- melt(data_type)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_type_mod <- data.frame(data_type_mod)
data_type_mod <- na.omit(data_type_mod)
data_type_mod <- remove_labels(data_type_mod)
ggwithinstats(
data = data_type_mod,
x = variable,
y = value,
xlab = "Children vs. animals vs. trees",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Comparing all conditions",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
Certainty (H6)
- H6a - equivalent net outcome, medium risk.
- H6b - different net outcomes, high reward for risk.
- H6c - equivalent net outcome, high risk.
- H6d - different net outcomes, small reward for risk.
10 save 100% vs. 20 save 50% (H6a) - equivalent net outcome, medium risk.
Charities A and B both save lives. Per each $2,000 spent, Charity A saves 10 people with absolute certainty (100%). Per each $2,000 spent, Charity B has a 50% chance of saving 20 people, and a 50% chance of not saving any lives at all (0). Imagine that you have $20,000 to allocate between the two charities.
H6a: Risk aversion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -17.25422 114.0000 < .0000001 -30.60870 Cohen's d -1.608964 -1.884676 -1.330003
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 19.39130 20.00000 19.02385 1.773983
## ─────────────────────────────────────────────────────────────────────────────
10 save 100% vs. 20 save 80% (H6b) - different net outcomes, high reward for risk.
Charities A and B both save lives. Per each $2,000 spent, Charity A saves 10 people with absolute certainty (100%). Per each $2,000 spent, Charity B has an 80% chance of saving 20 people, and a 20% chance of not saving any lives at all (0). Imagine that you have $20,000 to allocate between the two charities.
H6b: Risk aversion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -4.894709 114.0000 0.0000033 -13.73913 Cohen's d -0.4564340 -0.6476353 -0.2634139
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 36.26087 40.00000 30.10102 2.806935
## ─────────────────────────────────────────────────────────────────────────────
1 save 100% vs. 10 save 10% (H6c) - equivalent net outcome, high risk.
Charities A and B both save lives. Per each $2,000 spent, Charity A saves 1 person with absolute certainty (100%). Per each $2,000 spent, Charity B has a 10% chance of saving 10 people, and 90% chance of saving no people at all (0). Imagine that you have $20,000 to allocate between the two charities.
H6c: Risk aversion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -16.14295 114.0000 < .0000001 -33.21739 Cohen's d -1.505338 -1.771095 -1.236334
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 16.78261 0.000000 22.06640 2.057702
## ─────────────────────────────────────────────────────────────────────────────
75 save 100% vs. 100 save 80% (H6d) - different net outcomes, small reward for risk.
Charities A and B both save lives. Per each $2,000 spent, Charity A saves 75 people with absolute certainty (100%). Per each $2,000 spent, Charity B has an 80% chance of saving 100 people, and a 20% chance of not saving any lives at all (0). Imagine that you have $20,000 to allocate between the two charities.
H6d: Risk aversion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -10.21071 114.0000 < .0000001 -24.26087 Cohen's d -0.9521540 -1.171245 -0.7301365
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 25.73913 20.00000 25.47998 2.376021
## ─────────────────────────────────────────────────────────────────────────────
Comparing all conditions H6
Exploratory(not pre-registered): Note: Difficult to compare all the four conditions
H6a < H6b
jmv::anovaRM(
data = data,
rm = list(
list(
label="Certainty",
levels=c(
"10 save 100% vs. 20 save 50%",
"10 save 100% vs. 20 save 80%",
"1 save 100% vs. 10 save 10%",
"75 save 100% vs. 100 save 80%"))),
rmCells = list(
list(
measure="A18_1allocation",
cell="10 save 100% vs. 20 save 50%"),
list(
measure="A19_1allocation",
cell="10 save 100% vs. 20 save 80%"),
list(
measure="A20_1allocation",
cell="1 save 100% vs. 10 save 10%"),
list(
measure="A21_1allocation",
cell="75 save 100% vs. 100 save 80%")),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ Certainty,
postHoc = list(
"Certainty"),
emMeans = ~ Certainty,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## Certainty 25932.83 3 8644.2754 22.26292 < .0000001 0.0864416 0.1633821
## Residual 132792.17 342 388.2812
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 141279.1 114 1239.291
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - Certainty
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Certainty Certainty Mean Difference SE df t p-tukey
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## 10 save 100% vs. 20 save 50% - 10 save 100% vs. 20 save 80% -16.869565 2.806675 114.0000 -6.010516 0.0000001
## - 1 save 100% vs. 10 save 10% 2.608696 1.913806 114.0000 1.363093 0.5250276
## - 75 save 100% vs. 100 save 80% -6.347826 1.812451 114.0000 -3.502343 0.0036395
## 10 save 100% vs. 20 save 80% - 1 save 100% vs. 10 save 10% 19.478261 3.343638 114.0000 5.825469 0.0000003
## - 75 save 100% vs. 100 save 80% 10.521739 3.045156 114.0000 3.455238 0.0042467
## 1 save 100% vs. 10 save 10% - 75 save 100% vs. 100 save 80% -8.956522 2.288744 114.0000 -3.913290 0.0008837
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## CERTAINTY
##
## Estimated Marginal Means - Certainty
## ─────────────────────────────────────────────────────────────────────────────────
## Certainty Mean SE Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────
## 10 save 100% vs. 20 save 50% 19.39130 1.773983 15.87706 22.90555
## 10 save 100% vs. 20 save 80% 36.26087 2.806935 30.70035 41.82139
## 1 save 100% vs. 10 save 10% 16.78261 2.057702 12.70632 20.85890
## 75 save 100% vs. 100 save 80% 25.73913 2.376021 21.03225 30.44601
## ─────────────────────────────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_certainty <- data.frame(data$A18_1allocation,
data$A19_1allocation,
data$A20_1allocation,
data$A21_1allocation)
colnames(data_certainty) <- c("10 save 100% vs. 20 save 50%",
"10 save 100% vs. 20 save 80%",
"1 save 100% vs. 10 save 10%",
"75 save 100% vs. 100 save 80%")
data_certainty_mod <- melt(data_certainty)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_certainty_mod <- data.frame(data_certainty_mod)
data_certainty_mod <- na.omit(data_certainty_mod)
data_certainty_mod <- remove_labels(data_certainty_mod)
ggwithinstats(
data = data_certainty_mod,
x = variable,
y = value,
xlab = "Certainty",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Comparing all conditions",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
Risks (H7)
5 save 100% vs. 5000 save 0.1%
Charities A and B both save lives. Per each $2,000 spent, Charity A save 5 people with absolute certainty (100%). Per each $2,000 spent, Charity B has a 0.1% chance (1 in 1000) of saving 5,000 people, and a 99.9% chance of not saving any lives at all (0). Imagine that you have $20,000 to allocate between the two charities.
H7a: Risk aversion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -19.13485 114.0000 < .0000001 -36.86957 Cohen's d -1.784334 -2.077532 -1.487905
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 13.13043 0.000000 20.66293 1.926828
## ─────────────────────────────────────────────────────────────────────────────
5 save 100% vs. 500 save 1%
Charities A and B both save lives. Per each $2,000 spent, Charity A saves 5 people with absolute certainty (100%). Per each $2,000 spent, Charity B has a 1% chance (1 in 100) of saving 500 people, and a 99% chance of not saving any lives at all (0). Imagine that you have $20,000 to allocate between the two charities.
H7b: Risk aversion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -24.07189 114.0000 < .0000001 -38.78261 Cohen's d -2.244715 -2.586793 -1.899526
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 11.21739 0.000000 17.27730 1.611116
## ─────────────────────────────────────────────────────────────────────────────
5 save 100% vs. 50 save 10%
Charities A and B both save lives. Per each $2,000 spent, Charity A saves 5 people with absolute certainty (100%). Per each $2,000 spent, Charity B has a 10% (1 in 10) chance of saving 50 people, and a 90% chance of not saving any lives at all (0). Imagine that you have $20,000 to allocate between the two charities.
H7c: Risk aversion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -18.39822 114.0000 < .0000001 -33.47826 Cohen's d -1.715643 -2.001904 -1.426144
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 115 16.52174 10.00000 19.51353 1.819646
## ─────────────────────────────────────────────────────────────────────────────
Risk: Comparing all conditions H7
H7a+b+c: H7a > H7b > H7c
jmv::anovaRM(
data = data,
rm = list(
list(
label="Risk",
levels=c(
"5 save 100% vs. 5000 save 0.1%",
"5 save 100% vs. 500 save 1%",
"5 save 100% vs. 50 save 10%"))),
rmCells = list(
list(
measure="A22_1allocation",
cell="5 save 100% vs. 5000 save 0.1%"),
list(
measure="A23_1allocation",
cell="5 save 100% vs. 500 save 1%"),
list(
measure="A24_1allocation",
cell="5 save 100% vs. 50 save 10%")),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ Risk,
postHoc = list(
"Risk"),
emMeans = ~ Risk,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Risk 1659.710 2 829.8551 5.446326 0.0048916 0.0129897 0.0455964
## Residual 34740.290 228 152.3697
## ───────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 91371.01 114 801.5001
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - Risk
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Risk Risk Mean Difference SE df t p-tukey
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## 5 save 100% vs. 5000 save 0.1% - 5 save 100% vs. 500 save 1% 1.913043 1.595645 114.0000 1.198916 0.4562648
## - 5 save 100% vs. 50 save 10% -3.391304 1.852234 114.0000 -1.830927 0.1641601
## 5 save 100% vs. 500 save 1% - 5 save 100% vs. 50 save 10% -5.304348 1.404590 114.0000 -3.776440 0.0007393
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## RISK
##
## Estimated Marginal Means - Risk
## ───────────────────────────────────────────────────────────────────────────────────
## Risk Mean SE Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────
## 5 save 100% vs. 5000 save 0.1% 13.13043 1.926828 9.313404 16.94747
## 5 save 100% vs. 500 save 1% 11.21739 1.611116 8.025783 14.40900
## 5 save 100% vs. 50 save 10% 16.52174 1.819646 12.917033 20.12644
## ───────────────────────────────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_chances <- data.frame(data$A22_1allocation,
data$A23_1allocation,
data$A24_1allocation)
colnames(data_chances) <- c("5 save 100% vs. 5000 save 0.1%",
"5 save 100% vs. 500 save 1%",
"5 save 100% vs. 50 save 10%")
data_chances_mod <- melt(data_chances)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_chances_mod <- data.frame(data_chances_mod)
data_chances_mod <- na.omit(data_chances_mod)
data_chances_mod <- remove_labels(data_chances_mod)
ggwithinstats(
data = data_chances_mod,
x = variable,
y = value,
xlab = "Risk",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Risk: Comparing all conditions",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
H6+H7
Comparing all conditions H6+H7
jmv::anovaRM(
data = data,
rm = list(
list(
label="Certainty",
levels=c(
"10 save 100% vs. 20 save 50%",
"10 save 100% vs. 20 save 80%",
"1 save 100% vs. 10 save 10%",
"75 save 100% vs. 100 save 80%",
"5 save 100% vs. 5000 save 0.1%",
"5 save 100% vs. 500 save 1%",
"5 save 100% vs. 50 save 10%"))),
rmCells = list(
list(
measure="A18_1allocation",
cell="10 save 100% vs. 20 save 50%"),
list(
measure="A19_1allocation",
cell="10 save 100% vs. 20 save 80%"),
list(
measure="A20_1allocation",
cell="1 save 100% vs. 10 save 10%"),
list(
measure="A21_1allocation",
cell="75 save 100% vs. 100 save 80%"),
list(
measure="A22_1allocation",
cell="5 save 100% vs. 5000 save 0.1%"),
list(
measure="A23_1allocation",
cell="5 save 100% vs. 500 save 1%"),
list(
measure="A24_1allocation",
cell="5 save 100% vs. 50 save 10%")),
effectSize = c("eta", "partEta"),
depLabel = "% allocation to B",
rmTerms = ~ Certainty,
postHoc = list(
"Certainty"),
emMeans = ~ Certainty,
emmTables = TRUE,
emmPlotData = TRUE,
groupSumm = TRUE)## Warning: attributes are not identical across measure variables; they will be
## dropped##
## REPEATED MEASURES ANOVA
##
## Within Subjects Effects
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## Certainty 51102.36 6 8517.0600 27.47432 < .0000001 0.1132375 0.1942001
## Residual 212040.50 684 310.0007
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## Between Subjects Effects
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Sum of Squares df Mean Square F p η² η²-p
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Residual 188142.1 114 1650.369
## ────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Type 3 Sums of Squares
##
##
## POST HOC TESTS
##
## Post Hoc Comparisons - Certainty
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Certainty Certainty Mean Difference SE df t p-tukey
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## 10 save 100% vs. 20 save 50% - 10 save 100% vs. 20 save 80% -16.8695652 2.806675 114.0000 -6.0105159 0.0000005
## - 1 save 100% vs. 10 save 10% 2.6086957 1.913806 114.0000 1.3630930 0.8200320
## - 75 save 100% vs. 100 save 80% -6.3478261 1.812451 114.0000 -3.5023429 0.0114273
## - 5 save 100% vs. 5000 save 0.1% 6.2608696 1.954716 114.0000 3.2029567 0.0284280
## - 5 save 100% vs. 500 save 1% 8.1739130 1.631977 114.0000 5.0085945 0.0000409
## - 5 save 100% vs. 50 save 10% 2.8695652 1.561186 114.0000 1.8380670 0.5254785
## 10 save 100% vs. 20 save 80% - 1 save 100% vs. 10 save 10% 19.4782609 3.343638 114.0000 5.8254692 0.0000011
## - 75 save 100% vs. 100 save 80% 10.5217391 3.045156 114.0000 3.4552382 0.0132605
## - 5 save 100% vs. 5000 save 0.1% 23.1304348 3.378862 114.0000 6.8456288 < .0000001
## - 5 save 100% vs. 500 save 1% 25.0434783 3.125579 114.0000 8.0124287 < .0000001
## - 5 save 100% vs. 50 save 10% 19.7391304 3.123350 114.0000 6.3198588 0.0000001
## 1 save 100% vs. 10 save 10% - 75 save 100% vs. 100 save 80% -8.9565217 2.288744 114.0000 -3.9132905 0.0028840
## - 5 save 100% vs. 5000 save 0.1% 3.6521739 1.765551 114.0000 2.0685750 0.3783874
## - 5 save 100% vs. 500 save 1% 5.5652174 1.898216 114.0000 2.9318148 0.0602381
## - 5 save 100% vs. 50 save 10% 0.2608696 1.875047 114.0000 0.1391269 0.9999994
## 75 save 100% vs. 100 save 80% - 5 save 100% vs. 5000 save 0.1% 12.6086957 2.411158 114.0000 5.2293110 0.0000159
## - 5 save 100% vs. 500 save 1% 14.5217391 2.037945 114.0000 7.1256787 < .0000001
## - 5 save 100% vs. 50 save 10% 9.2173913 2.164648 114.0000 4.2581470 0.0008218
## 5 save 100% vs. 5000 save 0.1% - 5 save 100% vs. 500 save 1% 1.9130435 1.595645 114.0000 1.1989158 0.8932486
## - 5 save 100% vs. 50 save 10% -3.3913043 1.852234 114.0000 -1.8309268 0.5302268
## 5 save 100% vs. 500 save 1% - 5 save 100% vs. 50 save 10% -5.3043478 1.404590 114.0000 -3.7764399 0.0046313
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##
##
## ESTIMATED MARGINAL MEANS
##
## CERTAINTY
##
## Estimated Marginal Means - Certainty
## ───────────────────────────────────────────────────────────────────────────────────
## Certainty Mean SE Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────
## 10 save 100% vs. 20 save 50% 19.39130 1.773983 15.877057 22.90555
## 10 save 100% vs. 20 save 80% 36.26087 2.806935 30.700353 41.82139
## 1 save 100% vs. 10 save 10% 16.78261 2.057702 12.706316 20.85890
## 75 save 100% vs. 100 save 80% 25.73913 2.376021 21.032252 30.44601
## 5 save 100% vs. 5000 save 0.1% 13.13043 1.926828 9.313404 16.94747
## 5 save 100% vs. 500 save 1% 11.21739 1.611116 8.025783 14.40900
## 5 save 100% vs. 50 save 10% 16.52174 1.819646 12.917033 20.12644
## ───────────────────────────────────────────────────────────────────────────────────
##
##
## Group Summary
## ────────────────────────
## N Excluded
## ────────────────────────
## 115 376
## ────────────────────────
data_h6h7 <- data.frame(data$A18_1allocation,
data$A19_1allocation,
data$A20_1allocation,
data$A21_1allocation,
data$A22_1allocation,
data$A23_1allocation,
data$A24_1allocation)
colnames(data_h6h7) <- c( "10 save 100% vs. 20 save 50%",
"10 save 100% vs. 20 save 80%",
"1 save 100% vs. 10 save 10%",
"75 save 100% vs. 100 save 80%",
"5 save 100% vs. 5000 save 0.1%",
"5 save 100% vs. 500 save 1%",
"5 save 100% vs. 50 save 10%")
data_h6h7_mod <- melt(data_h6h7)## No id variables; using all as measure variables## Warning: attributes are not identical across measure variables; they will be
## droppeddata_h6h7_mod <- data.frame(data_h6h7_mod)
data_h6h7_mod <- na.omit(data_h6h7_mod)
data_h6h7_mod <- remove_labels(data_h6h7_mod)
ggwithinstats(
data = data_h6h7_mod,
x = variable,
y = value,
xlab = "Risk",
ylab = "% allocation to B",
plot.type = "boxviolin",
title = "Risk: Comparing all conditions",
point.args = list(size = 3, alpha = 0.2, position =
ggplot2::position_jitterdodge(jitter.width = 0.4,
jitter.height = 3)),
ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
type = "parametric"
)## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
Analyses: Individual scenarios
Pre-registration general criteria: Alpha (p-values) = .001
Tax deduction (H11)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Donations to Charity A do not qualify for tax deductions, donations to Charity B qualify for tax deductions.
H11: tax deduction > no tax deduction (>50) (Note: corrected mistake in the pre-registration: that had “tax deducation > tax deducation (>50)” )
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 5.558755 118.0000 0.0000002 14.62185 Cohen's d 0.5095702 0.3175640 0.6996572
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 119 64.62185 60.00000 28.69447 2.630418
## ─────────────────────────────────────────────────────────────────────────────
Common in region (H12)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A addresses causes of death more common in your region of residence. Charity B addresses causes of death that are less common in your region of residence.
H12: Common in region > less common in region (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -6.883978 95.00000 < .0000001 -13.95833 Cohen's d -0.7025931 -0.9246322 -0.4775600
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 96 36.04167 40.00000 19.86688 2.027655
## ────────────────────────────────────────────────────────────────────────────
Norms (H13)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). You learn that 80% of the people who donated in your city donated to Charity A, whereas only 20% of the people who donated in your city donated to Charity B.
H13: 80% in city > 20% in city (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 4.269553 105.0000 0.0000431 11.03774 Cohen's d 0.4146957 0.2153442 0.6122251
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 61.03774 60.00000 26.61647 2.585220
## ─────────────────────────────────────────────────────────────────────────────
Treatment vs. Preventive (H14)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent) addressing the same disease. Charity A aims to treat patients who have already been infected by the disease. Charity B aims to vaccinate people to prevent people from contracting the disease, being severely affected by the disease, or dying from the disease in the future.
H14: Treatment > Preventive (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 1.014457 118.0000 0.3124403 2.352941 Cohen's d 0.09299513 -0.08726066 0.2728566
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 119 52.35294 50.00000 25.30177 2.319409
## ─────────────────────────────────────────────────────────────────────────────
Information/Updates (H15)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is a registered charity that provides public weekly updates regarding its activities on their website and issues public annual reports of their impact and progress. Charity B is a registered charity that provides weekly updates regarding its activities and annual reports, yet only to donors and monitoring government agencies.
H15: With information updates > without updates (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -7.416740 104.0000 < .0000001 -16.28571 Cohen's d -0.7237997 -0.9374357 -0.5073796
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 105 33.71429 40.00000 22.50031 2.195805
## ─────────────────────────────────────────────────────────────────────────────
Well established vs. New (H16)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A funds the latest approved drugs on the market using the latest developments, which may or may not be more effective than the commonly used drugs. Charity B funds the use of the commonly used drugs that are well-established and have been shown to be moderately effective.
Competing (exploratory) H16a: Well established > Latest development (>50) H16b: Well established < Latest development (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 4.339680 105.0000 0.0000329 10.28302 Cohen's d 0.4215070 0.2218811 0.6192868
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 60.28302 50.00000 24.39584 2.369534
## ─────────────────────────────────────────────────────────────────────────────
Optimism (H17)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A’s describes the victims it supports as sad and feeling pessimistic about having a better future. Charity B describes the victims it supports as sad yet optimistic about having a better future.
H17: Optimistic > Pessimistic (>50)
(Note: pre-registration had an oversight, optimistic is Charity B and therefore should be >50 and not <50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 3.235016 120.0000 0.0015718 6.528926 Cohen's d 0.2940924 0.1114912 0.4755186
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 121 56.52893 50.00000 22.20025 2.018205
## ─────────────────────────────────────────────────────────────────────────────
Neglectedness (H18)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A addresses a problem that is also being addressed by 100 other charities. Charity B addresses a problem that no other charity currently addresses.
H18: Neglectedness > Common (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 13.39866 85.00000 < .0000001 33.60465 Cohen's d 1.444815 1.139849 1.745451
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 86 83.60465 90.00000 23.25879 2.508060
## ────────────────────────────────────────────────────────────────────────────
Gender (H19)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A targets helping female victims. Charity B targets helping male victims.
H19: Females > Males (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -5.741107 116.0000 < .0000001 -10.17094 Cohen's d -0.5307655 -0.7233749 -0.3361439
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 117 39.82906 50.00000 19.16277 1.771599
## ─────────────────────────────────────────────────────────────────────────────
Charity message f raming (H20)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A states in its campaign that “With your donation, children’s lives will be saved.” Charity B states in its campaign that “Without your donation, children’s lives will be lost”.
H20: Negative > Positive (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -6.658706 105.0000 < .0000001 -13.96226 Cohen's d -0.6467507 -0.8549277 -0.4360061
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 36.03774 50.00000 21.58832 2.096843
## ─────────────────────────────────────────────────────────────────────────────
Recency (H21)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A aims to save refugees yet does not specify where the refugees are from. Charity B aims to save refugees from the most recent unfolding crisis you saw broadcast on the media.
H21: Recency > Unspecified (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 3.775019 107.0000 0.0002631 8.796296 Cohen's d 0.3632514 0.1676898 0.5572143
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 108 58.79630 50.00000 24.21545 2.330133
## ─────────────────────────────────────────────────────────────────────────────
Direct cash transfer vs. supplies (H22)
Charities A and B both help impoverished families in developing countries improve their lives. Charity A transfers the cash you donated directly to the identified and verified families in need. Charity B provides food and medicine supplies (worth the same amount as what you donated) to the identified and verified families in need.
H22: Supplies > Direct cash transfer (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 3.631807 105.0000 0.0004371 10.18868 Cohen's d 0.3527523 0.1557208 0.5482030
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 60.18868 50.00000 28.88338 2.805402
## ─────────────────────────────────────────────────────────────────────────────
Food vs. Textbooks (H23)
Charities A and B both aim to help children. Charity A provides food. Charity B provides school textbooks.
H23: Food > textbooks (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -8.395500 113.0000 < .0000001 -16.31579 Cohen's d -0.7863106 -0.9951625 -0.5747687
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 114 33.68421 30.00000 20.74980 1.943397
## ─────────────────────────────────────────────────────────────────────────────
Promotion (H24)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A does not actively seek donations. Charity B actively seeks donations through various approaches (i.e., promotion booths, door-to-door, online media, campaigns, etc.).
H24: No promotion > Promotion (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -3.719050 117.0000 0.0003085 -8.644068 Cohen's d -0.3423663 -0.5273498 -0.1559976
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 118 41.35593 50.00000 25.24801 2.324268
## ─────────────────────────────────────────────────────────────────────────────
Subscription (H25)
Charities A and B both save the lives of 5 children with $1,200 each year. Charity A accepts donations using single payments of $1,200. Charity B accepts donations using an annual monthly subscription model, with a payment of $100 each month for a period of one year ($1,200 total). Assume zero inflation throughout the year and that subscriptions end after one year. Imagine that you have $12,000 (10 donations of $1,200) to allocate between the two charities.
H25: One payment > Subscription (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -0.03746371 94.00000 0.9701947 -0.1052632 Cohen's d -0.003843696 -0.2049224 0.1972554
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 95 49.89474 50.00000 27.38592 2.809736
## ────────────────────────────────────────────────────────────────────────────
H25 (reversed): One payment < Subscription (<50)
(not pre-registered, just for presentation purposes)
Calculating a new reversed variable and rerunning the analysis.
data$A15_2allocation_recorded = 100 - data$A15_2allocation
AnalyzeComparison(data, "A15_2allocation_recorded", "Subscription", 50)##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 0.03746371 94.00000 0.9701947 0.1052632 Cohen's d 0.003843696 -0.1972554 0.2049224
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 95 50.10526 50.00000 27.38592 2.809736
## ────────────────────────────────────────────────────────────────────────────
Proportion 1 Refugee camp (H26)
Charities A and B both have the means to save 1,000 lives of those in refugee camps in a third-world country, yet each charity can only help one refugee camp. Charity A saves 1,000 lives in refugee camp of 10,000 people. Charity B saves 1,000 people in a refugee camp with 1,000,000 people.
H26: High proportion (Smaller camp) > Low proportion (Larger camp) (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -2.708163 97.00000 0.0079977 -6.326531 Cohen's d -0.2735658 -0.4745701 -0.07120322
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 98 43.67347 50.00000 23.12618 2.336097
## ────────────────────────────────────────────────────────────────────────────
US vs. Africa (H27)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A aims to save lives in your home country. Charity B aims to saves lives in Africa.
H27: Ingroup > Outgroup (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -6.203711 109.0000 < .0000001 -15.09091 Cohen's d -0.5915007 -0.7930040 -0.3876735
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 110 34.90909 40.00000 25.51292 2.432561
## ─────────────────────────────────────────────────────────────────────────────
Personal relevance: Loved ones (H28)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A aims to help those suffering from a disease that one of your loved ones is suffering from. Charity B aims to help those suffering from a disease that no one you know suffers from.
H28: Personal relevance > No relevance (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -9.787078 105.0000 < .0000001 -21.50943 Cohen's d -0.9506050 -1.178648 -0.7193891
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 28.49057 30.00000 22.62710 2.197738
## ─────────────────────────────────────────────────────────────────────────────
Personal relevance: Own risk (H29)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A aims to help those suffering from a disease that you are considered to be at high risk of suffering from, whereas Charity B aims to help those suffering from a disease that as far as you know is of no risk to you.
H29: Personal relevance > No relevance (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -8.800745 93.00000 < .0000001 -19.25532 Cohen's d -0.9077275 -1.146466 -0.6654795
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 94 30.74468 30.00000 21.21266 2.187919
## ────────────────────────────────────────────────────────────────────────────
Regular media / Social media (H30)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A has appeared on the news/media 10 times in 2023 and had 1 million followers on Instagram at the end of 2023. Charity B has appeared on the news/media 30 times in 2023 and has 2000 followers on Instagram at the end of 2023.
H30: Regular media > Social media (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 1.221168 108.0000 0.2246816 2.293578 Cohen's d 0.1169667 -0.07167819 0.3050726
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 109 52.29358 50.00000 19.60881 1.878184
## ─────────────────────────────────────────────────────────────────────────────
Immediate relief vs. root causes (H31)
Charities A and B both address poverty. Charity A aims to address the desperate need for immediate relief. It provides life-saving aid such as food, clean water, medical supplies, and shelter to the villagers. Charity B aims addresses root causes, investing in long-term solutions, such as education programs, agricultural initiatives, and healthcare infrastructure, to support the entire region and break the cycle of poverty.
H31: Immediate relief > Root causes (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 0.7395063 108.0000 0.4612040 1.651376 Cohen's d 0.07083186 -0.1173008 0.2586357
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 109 51.65138 50.00000 23.31403 2.233079
## ─────────────────────────────────────────────────────────────────────────────
Local endorsement (H32)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A receives the support and endorsement of the local population. It is unknown who supports and endorses Charity B.
H32: Local endorsement > No endorsement (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -10.19275 108.0000 < .0000001 -22.38532 Cohen's d -0.9762886 -1.203100 -0.7463557
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 109 27.61468 30.00000 22.92900 2.196200
## ─────────────────────────────────────────────────────────────────────────────
Rare vs. Frequent (H33)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A aims to help victims of rare disasters (e.g., strong earthquakes, tsunamis, etc.). Charity B aims to help victims of more frequent disasters (e.g., typhoons, droughts, etc.)
H33: Rare < Frequent (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 3.996795 116.0000 0.0001132 5.982906 Cohen's d 0.3695038 0.1814370 0.5560771
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 117 55.98291 50.00000 16.19173 1.496926
## ─────────────────────────────────────────────────────────────────────────────
H33 (reversed): Rare > Frequent (>50)
(not pre-registered, just for presentation purposes)
Calculating a new reversed variable and rerunning the analysis.
data$A23_2allocation_recorded = 100 - data$A23_2allocation
AnalyzeComparison(data, "A23_2allocation_recorded", "Rare vs. Frequent", 50)##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -3.996795 116.0000 0.0001132 -5.982906 Cohen's d -0.3695038 -0.5560771 -0.1814370
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 117 44.01709 50.00000 16.19173 1.496926
## ─────────────────────────────────────────────────────────────────────────────
Familiarity (H34)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is very well known. Charity B is not very well known.
H34: Familiar < Less familiar (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -1.150559 108.0000 0.2524548 -2.568807 Cohen's d -0.1102036 -0.2982539 0.07835570
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 109 47.43119 50.00000 23.30966 2.232660
## ─────────────────────────────────────────────────────────────────────────────
Charity age (H35)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A was established in 2023. Charity B was established in 1960.
H35: Older > Newer (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 4.658227 104.0000 0.0000095 8.476190 Cohen's d 0.4545965 0.2526233 0.6545827
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 105 58.47619 50.00000 18.64553 1.819617
## ─────────────────────────────────────────────────────────────────────────────
Shared beliefs 1 (H36)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A aims to help people who share the same beliefs and values as you do. Charity B aims to help people who you know nothing about.
H36: Shared beliefs > No info (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -5.754675 89.00000 0.0000001 -13.33333 Cohen's d -0.6065960 -0.8300960 -0.3802006
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 90 36.66667 40.00000 21.98058 2.316957
## ────────────────────────────────────────────────────────────────────────────
Shared beliefs 2 (H37)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A aims to help people who do not share your beliefs and values. Charity B helps people whose beliefs and values you know nothing about.
H37: No info > No shared beliefs (>50)
(Note: Pre-registation had an oversight, the no-info is charity B and therefore should have been >50 and not <50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 3.171665 102.0000 0.0020025 7.572816 Cohen's d 0.3125134 0.1139692 0.5095963
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 103 57.57282 50.00000 24.23197 2.387647
## ─────────────────────────────────────────────────────────────────────────────
Direct versus indirect cash transfers (H38)
Charity A gives unconditional cash transfers directly to those it has identified and verified as being in need. Charity B transfers funding to a local verified authority that then identifies and verifies those in need and is in charge of the unconditional cash transfers to the recipients.
H38: Indirect > Direct (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -3.175211 119.0000 0.0019067 -8.666667 Cohen's d -0.2898558 -0.4719329 -0.1066095
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 120 41.33333 50.00000 29.89993 2.729477
## ─────────────────────────────────────────────────────────────────────────────
Single vs. multiple causes (H39)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is solely focused on a single important cause. Charity B addresses three different equally important causes (and equally important as the single cause addressed by Charity A).
H39: multiple > single causes (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.176840 113.0000 0.0315728 5.350877 Cohen's d 0.2038797 0.01796024 0.3889159
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 114 55.35088 50.00000 26.24526 2.458094
## ─────────────────────────────────────────────────────────────────────────────
Other donations (H40)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A receives donations from 1000 people every day. Charity B receives donations from 100 people every day.
H40: 1000 > 100 (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 8.674683 112.0000 < .0000001 21.32743 Cohen's d 0.8160455 0.6016132 1.027709
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 113 71.32743 80.00000 26.13510 2.458584
## ─────────────────────────────────────────────────────────────────────────────
Donation amount (H41)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A receives a certain amount from donations every day. Charity B receives donations 10 times the amount that Charity A receives from donations each day.
H41: 10x > X (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -11.07826 94.00000 < .0000001 -27.57895 Cohen's d -1.136605 -1.393102 -0.8763406
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 95 22.42105 20.00000 24.26432 2.489466
## ────────────────────────────────────────────────────────────────────────────
Celebrity endorsement (H42)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is endorsed by a celebrity you recognize. You are unaware of any celebrities endorsing Charity B.
H42: Celebrity endorsement > No celebrity endorsement (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.092270 99.00000 0.0389724 4.900000 Cohen's d 0.2092270 0.01056449 0.4068561
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 100 54.90000 50.00000 23.41954 2.341954
## ─────────────────────────────────────────────────────────────────────────────
Thank you notes (H43)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A issues all its donors thank-you letters. Charity B does not issue thank-you letters to its donors.
H43: Thank you notes > No thank you notes (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -1.065683 105.0000 0.2890114 -2.452830 Cohen's d -0.1035083 -0.2941449 0.08761963
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 47.54717 50.00000 23.69695 2.301651
## ─────────────────────────────────────────────────────────────────────────────
Donor background: Wealthy (H44)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A donations have so far mostly come from wealthy donors. You do not know anything about the wealth of the donors of Charity B.
H44: Wealthy = No info (50; null)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 4.237118 93.00000 0.0000533 8.297872 Cohen's d 0.4370253 0.2242892 0.6476116
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 94 58.29787 50.00000 18.98717 1.958377
## ────────────────────────────────────────────────────────────────────────────
Donor background: Lower class (H45)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A donations have so far mostly come from working-class and lower-class donors. You do not know anything about the wealth of the donors of Charity B.
H45: Lower class = No info (50; null)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -5.355547 107.0000 0.0000005 -10.18519 Cohen's d -0.5153377 -0.7150825 -0.3134590
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 108 39.81481 50.00000 19.76410 1.901801
## ─────────────────────────────────────────────────────────────────────────────
Reputation (H46)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A has been consistently rated as trustworthy by a charity monitor think tank. Charity B has been rated as lower in trustworthiness than Charity A by the same charity monitor think tank.
H46: Reputation > Lower reputation (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -15.19737 90.00000 < .0000001 -32.52747 Cohen's d -1.593117 -1.901249 -1.280881
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 91 17.47253 10.00000 20.41750 2.140335
## ────────────────────────────────────────────────────────────────────────────
Personal case studies vs. evidence (H47)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A communications focuses on sharing interviews with its donation recipients, detailing recipients’ perspectives on how the donation improved their lives. Charity B communications focuses on sharing evidence, statistics, and facts regarding the impact of its donations.
H47: Personal case studies > evidence (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.307044 106.0000 0.0229961 5.046729 Cohen's d 0.2230303 0.03068213 0.4143527
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 107 55.04673 50.00000 22.62799 2.187531
## ─────────────────────────────────────────────────────────────────────────────
Refund bonuses (H48)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent) and both aim to crowdfund a certain needed amount of money to execute their missions. Both charities have a refund policy if the fundraising target is unmet. If fundraising target is unmet, Charity A gives a refund bonus, which is additional money in proportion to the donation, in excess of its refund amount. If fundraising target is unmet, Charity B only refunds the amount donated.
H48: Refund bonuses > Regular refund (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -2.749098 125.0000 0.0068620 -6.984127 Cohen's d -0.2449091 -0.4216552 -0.06721215
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 126 43.01587 50.00000 28.51722 2.540516
## ─────────────────────────────────────────────────────────────────────────────
Information sharing (H49)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A shares all information about its operations, resource allocation, and activities with its donors, recipients, and the general public. Charity B does not share any information about its operations, resource allocation and activities.
H49: Information sharing > No information sharing (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -16.79923 102.0000 < .0000001 -35.72816 Cohen's d -1.655277 -1.951377 -1.355554
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 103 14.27184 0.000000 21.58440 2.126774
## ─────────────────────────────────────────────────────────────────────────────
Share success stories (H50)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A shares success stories and testimonials from beneficiaries on their website and social media platforms. Charity B does not share success stories and testimonials.
H50: Shares success stories > No sharing success stories (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -6.422914 100.0000 < .0000001 -15.24752 Cohen's d -0.6391039 -0.8519164 -0.4236210
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 101 34.75248 40.00000 23.85766 2.373926
## ─────────────────────────────────────────────────────────────────────────────
Norms 2 (H51)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). You’ve learned that Charity A has received donations by many others you know in your area (neighborhood, city, etc.). You have no information about who donated to Charity B.
H51: Normative > No info (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -5.416853 101.0000 0.0000004 -12.74510 Cohen's d -0.5363484 -0.7428333 -0.3275327
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 102 37.25490 50.00000 23.76272 2.352860
## ─────────────────────────────────────────────────────────────────────────────
Reputation 2 (H52)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is widely recognized in the public domain, with positive reviews, and an accreditation. Charity B is not widely recognized in the public domain with limited reviews and is not accredited. H52: Reputation > No reputation (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -12.31807 97.00000 < .0000001 -28.06122 Cohen's d -1.244313 -1.506597 -0.9783027
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 98 21.93878 20.00000 22.55157 2.278053
## ────────────────────────────────────────────────────────────────────────────
Advertisements (H53)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A uses compelling and visually stimulating advertisements emphasizing the distressing situations of the donation targets. Charity B does not make use of advertisements to promote their cause.
H53: Advertisements > No advertisements (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.364189 124.0000 0.0196226 5.680000 Cohen's d 0.2114595 0.03377739 0.3883081
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 125 55.68000 50.00000 26.86093 2.402515
## ─────────────────────────────────────────────────────────────────────────────
Matching (H54)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Donations to Charity A are matched by donations of the same amount from a third party. Donations to Charity B are not matched by a third party.
H54: Matching > No matching (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -7.707944 96.00000 < .0000001 -23.81443 Cohen's d -0.7826231 -1.008696 -0.5533952
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 97 26.18557 20.00000 30.42899 3.089596
## ────────────────────────────────────────────────────────────────────────────
Attention (H55)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A focuses on an issue that is widely covered in world news and media. Charity B focuses on an issue that does not receive much attention from world news and media. You personally deem the two issues to be equally important.
H55: Attention > Less attention (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 3.272433 92.00000 0.0015024 7.419355 Cohen's d 0.3393355 0.1294097 0.5475165
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 93 57.41935 50.00000 21.86437 2.267229
## ────────────────────────────────────────────────────────────────────────────
Planting trees vs. Supporting local communities (H56)
Charities A and B both focus on environmental conservation and combating deforestation in the Amazon rain-forest. Charity A plants a large number of native tree species within a designated region of the Amazon rain-forest. Charity B works closely with local indigenous communities within the rain-forest, providing support for sustainable livelihoods.
H56: Supporting local communities > Planting trees (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 1.993129 138.0000 0.0482193 4.244604 Cohen's d 0.1690550 0.001322005 0.3361851
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 139 54.24460 50.00000 25.10784 2.129619
## ─────────────────────────────────────────────────────────────────────────────
Receipient effort (H57)
Charities A and B both combat poverty with the same effectiveness (lives helped per dollar spent). Charity A focuses on helping those who have shown themselves to make an effort and have invested much hard work in bettering their own conditions and trying to lift themselves out of poverty. Charity B helps all those identified and verified to be in need.
H57: Effort > All (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -2.009827 108.0000 0.0469428 -5.137615 Cohen's d -0.1925065 -0.3815430 -0.002596244
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 109 44.86239 50.00000 26.68800 2.556247
## ─────────────────────────────────────────────────────────────────────────────
Recipient details (H58)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A shares with donors details of those helped by their donation (name, photo, conditions, etc.). Charity B does not provide donors with any specific information about those helped by their donations.
H58: Recipient details > No recipient details (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -2.980440 103.0000 0.0035913 -8.173077 Cohen's d -0.2922561 -0.4878538 -0.09529790
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 104 41.82692 50.00000 27.96546 2.742239
## ─────────────────────────────────────────────────────────────────────────────
Religious affiliation (H59)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is affiliated with a religious institution. Charity B is not affiliated with a religious institution.
H59: Religious affiliation > No religious affiliation (<50)
(Note: the pre-registration indicated “>50”, althought the hypothesis was for religious > not religious and Charity A having religious affiliation and B without. This was an oversight, and corrected here to “<50”)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 7.163684 100.0000 < .0000001 19.50495 Cohen's d 0.7128132 0.4928186 0.9299397
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 101 69.50495 70.00000 27.36334 2.722754
## ─────────────────────────────────────────────────────────────────────────────
Personal experience (H60)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A supports a cause that you have had some personal experience with. Charity B supports a cause that you have not had any personal experience with.
H60: Personal experience > No personal experience (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -13.40219 106.0000 < .0000001 -22.42991 Cohen's d -1.295639 -1.551296 -1.036542
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 107 27.57009 30.00000 17.31185 1.673600
## ─────────────────────────────────────────────────────────────────────────────
Law risky (H61)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A operates in a country with strict laws against non-local charities and is constantly facing risks of a crackdown by the local government. Charity B operates in a country that is less strict about non-local charities and is facing lower risks of a crackdown on by the local government. Both countries have millions of people in dire need of help and are at risk of dying if not helped. In both countries, people in need are not helped by their local governments.
H61: Law risky > Less law risky (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 0.3649164 99.00000 0.7159522 0.9000000 Cohen's d 0.03649164 -0.1596636 0.2324594
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 100 50.90000 50.00000 24.66319 2.466319
## ─────────────────────────────────────────────────────────────────────────────
Local government funding (H62)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A receives substantial funding support from the local government on top of the funding from private donors. Charity B receives no funding support from the local government, meaning that all funding comes from private donors.
H62: Local government funding > No local government funding (<50)
(Note: the pre-registration had a mistake indicating “>50”, yet according to the scenario A is local funding and B is no local funding and therefore this should have been <50. Corrected here. Should be noted as a deviation)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 6.323812 104.0000 < .0000001 17.90476 Cohen's d 0.6171409 0.4070748 0.8246977
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 105 67.90476 70.00000 29.01244 2.831324
## ─────────────────────────────────────────────────────────────────────────────
Operational (H63)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is already operational and so funding will be used immediately. Charity B has everything in place to begin working and has already received approval that would allow it to begin operations in a year.
H63: Operational > Not yet operational (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -6.344646 104.0000 < .0000001 -15.04762 Cohen's d -0.6191740 -0.8268389 -0.4089944
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 105 34.95238 40.00000 24.30273 2.371704
## ─────────────────────────────────────────────────────────────────────────────
Remedy vs. Preventive (H64r)
Charities A and B both focus on flood damage and are of similar effectiveness (lives saved per dollar spent). Charity A focuses on preventive measures to prevent floods from happening. Charity B focuses on remedy measures to address floods when they happen.
H64: Remedy > Preventive (>50) (Reverse)
Recoded to H64r: Remedy > Preventive (<50)
data$A54_2allocation_recoded <- 100- data$A54_2allocation
AnalyzeComparison(data, "A54_2allocation_recoded", "Remedy vs. Preventive", 50)##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 5.155268 100.0000 0.0000013 10.99010 Cohen's d 0.5129684 0.3042833 0.7193783
## ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 101 60.99010 50.00000 21.42452 2.131819
## ─────────────────────────────────────────────────────────────────────────────
Lottery vs. First come (H65)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent) using unconditional cash transfers. Charity A allocates money using a random lottery among all identified and verified victims. Charity B allocates money using a first-come-first-served for all identified and verified victims.
H65: Lottery > First come (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.294798 117.0000 0.0235274 6.101695 Cohen's d 0.2112533 0.02836785 0.3932562
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 118 56.10169 50.00000 28.88332 2.658925
## ─────────────────────────────────────────────────────────────────────────────
US region vs. not in region (H66)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A focuses on victims in countries located in the region of your home country (though not including your own country). Charity B focuses on victims from countries that are far from the region of your home country.
H66: Proximate > Distant (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -5.977463 104.0000 < .0000001 -13.33333 Cohen's d -0.5833406 -0.7891502 -0.3751223
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 105 36.66667 50.00000 22.85686 2.230601
## ─────────────────────────────────────────────────────────────────────────────
Minorities vs. all (H67)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A focuses on helping victims from ethnic minorities in your community. Charity B focuses on victims in general, of all ethnicities.
H67: All > Minorities (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.840370 98.00000 0.0054806 7.575758 Cohen's d 0.2854679 0.08378175 0.4857561
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 99 57.57576 50.00000 26.53803 2.667173
## ────────────────────────────────────────────────────────────────────────────
Train vs. Planes with offsets (H68)
Charities A and B are both focused on environmental protection with the same effectiveness (same estimated amount of carbon emissions reduced). Charity A employees travel to conferences by trains. Charity B employees fly by planes, yet offset their carbon emissions footprint by planting trees.
H68: Train > Planes offsets (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -2.842937 98.00000 0.0054401 -7.474747 Cohen's d -0.2857259 -0.4860212 -0.08403203
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 99 42.52525 50.00000 26.16055 2.629234
## ────────────────────────────────────────────────────────────────────────────
Familiarity 2 (H69)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is well-known and receives more donations. Charity B is lesser-known and receives fewer donations.
H69: Familiar > Less familiar (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 8.266306 121.0000 < .0000001 18.77049 Cohen's d 0.7483962 0.5462774 0.9480717
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 122 68.77049 70.00000 25.08096 2.270723
## ─────────────────────────────────────────────────────────────────────────────
Temporal proximity (H70)
Charity A supports education for one year for 10,000 African children set to take place in the upcoming year. Charity B supports education for one year for 10,000 African children, set to take place in five years time.
H70: Proximate > Distant (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -13.15617 105.0000 < .0000001 -28.11321 Cohen's d -1.277840 -1.533080 -1.019136
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 21.88679 20.00000 22.00057 2.136884
## ─────────────────────────────────────────────────────────────────────────────
Matching vs. refund (H71)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A pledges to match your donation. For example, when you donate X dollars, a foundation which cooperates with Charity A will also donate X dollars. Charity B cooperates with another foundation. If you donate X dollars to Charity B, then that foundation will refund you half the amount of your donation (X divided by 2).
H71: Matching > refund (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -8.349097 112.0000 < .0000001 -21.76991 Cohen's d -0.7854170 -0.9951303 -0.5729911
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 113 28.23009 30.00000 27.71765 2.607457
## ─────────────────────────────────────────────────────────────────────────────
Execution time (H72)
Charity A vaccinates 10 children within one month for $1,000. Charity B vaccinates 20 children within 2 months for $2000. Imagine you have $20,000 to allocate between the two charities.
H72: Sooner > Later (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -0.6576037 122.0000 0.5120316 -1.056911 Cohen's d -0.05929413 -0.2360539 0.1177057
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 123 48.94309 50.00000 17.82488 1.607215
## ─────────────────────────────────────────────────────────────────────────────
Level of sharing (H73)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A posts an annual report detailing its donation goals, work goals, and collaboration goals, whether these have been reached, and plans on how to improve (if goals have failed), on top of reports about its impact and events. Charity B posts an annual report about its impact and events.
H73: High sharing > Low sharing (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -8.368341 110.0000 < .0000001 -18.73874 Cohen's d -0.7942878 -1.006436 -0.5793604
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 111 31.26126 40.00000 23.59188 2.239242
## ─────────────────────────────────────────────────────────────────────────────
Side effects (H74)
Charity A focuses on providing a well-tested vaccination with 95% effectiveness to prevent the certain deaths of 95 out of every 100 people. However, the vaccination may cause 5 of 100 of those vaccinated to die from side-effects. Charity B focuses on providing an equally well-tested vaccination that has 90% effectiveness to prevent the certain deaths of 90 out of every 100 people, yet has no documented risk of death from side-effects.
(was intended as related to omission bias using a similar concept, but there is no action-inaction here)
H74: No side-effects > Side-effect (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 7.663607 102.0000 < .0000001 21.35922 Cohen's d 0.7551177 0.5345592 0.9727653
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 103 71.35922 80.00000 28.28595 2.787098
## ─────────────────────────────────────────────────────────────────────────────
Sharing previous donors (H75)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A provides information regarding the typical donation amounts by previous donors (without further details), and will include your donation information in future donations. Charity B does not provide any information regarding past donations.
H75a: No sharing > Sharing (>50) (People prefer anonymity) H75b: Sharing > No sharing (<50) (People prefer transparency)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -1.036784 94.00000 0.3024963 -3.052632 Cohen's d -0.1063718 -0.3077514 0.09556975
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 95 46.94737 50.00000 28.69775 2.944327
## ────────────────────────────────────────────────────────────────────────────
Designation (H76)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A has already identified children in need and a waiting list of children that are to be helped. Charity B only proceeds to identify the children in need and support them upon securing the donation.
H76: Designated > Not designated (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -7.746144 94.00000 < .0000001 -18.73684 Cohen's d -0.7947376 -1.023996 -0.5622295
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 95 31.26316 30.00000 23.57614 2.418861
## ────────────────────────────────────────────────────────────────────────────
Sharing on social media (H77)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A posts its impact, accomplishments, and progress on social media regularly. Charity B does not post any information on social media.
H77: Sharing > Not sharing (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -4.410489 110.0000 0.0000241 -10.72072 Cohen's d -0.4186250 -0.6118120 -0.2236842
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 111 39.27928 40.00000 25.60936 2.430733
## ─────────────────────────────────────────────────────────────────────────────
Friends donated (H78)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). You’ve learned that your friends have previously donated to Charity A. You do not know whether your friends donated to Charity B.
H78: Friends donated > No info (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -3.156821 116.0000 0.0020328 -4.358974 Cohen's d -0.2918482 -0.4762857 -0.1062036
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 117 45.64103 50.00000 14.93576 1.380811
## ─────────────────────────────────────────────────────────────────────────────
Giving multiplier (H79)
Charities A and B both address a social issue that is personally and emotionally appealing to you. Charity A leverages 100% of your donation to tackle a social issue that you care about. Charity B leverages 50% of your donation to tackle the social issue that you care about; remaining 50% is to other projects with guaranteed higher cost-effectiveness but is not particularly appealing to you, yet is matched by donations of another donor, for every dollar of the 50% of your donations, an external donor puts in another dollar.
H79: Giving multiplier with matching > Regular (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -5.389185 113.0000 0.0000004 -15.78947 Cohen's d -0.5047434 -0.6987308 -0.3087672
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 114 34.21053 30.00000 31.28218 2.929845
## ─────────────────────────────────────────────────────────────────────────────
Recepients’ mood presentation (H80)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A tends to present those they aim to support as being happy and joyful. Charity B tends to present those they aim to support as being sad and miserable.
H80a: Happy and joyful > Sad and miserable (<50) (more relatedness) H80b: Happy and joyful < Sad and miserable (>50) (more empathy)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -1.150677 101.0000 0.2525820 -2.745098 Cohen's d -0.1139340 -0.3083530 0.08104705
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 102 47.25490 50.00000 24.09375 2.385636
## ─────────────────────────────────────────────────────────────────────────────
Diversification: Single vs multiple treatments (H81)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A is solely focused on a single treatment. Charity B employs three different equally effective treatments (and equally effective as the single treatment used by Charity A).
H81: Multiple treatments (diversification) > Single treatment (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 6.011184 111.0000 < .0000001 11.51786 Cohen's d 0.5680035 0.3672244 0.7665702
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 112 61.51786 55.00000 20.27779 1.916071
## ─────────────────────────────────────────────────────────────────────────────
Local US community vs. Africa (H82)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent) by supporting poor families. Charity A supports poor families in the local community. Charity B supports poor families in Africa.
H82: Ingroup > Outgroup (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -7.805952 100.0000 < .0000001 -19.80198 Cohen's d -0.7767212 -0.9979059 -0.5525195
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 101 30.19802 30.00000 25.49432 2.536780
## ─────────────────────────────────────────────────────────────────────────────
Infrastructures vs. direct unconditional cash transfers (H83)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent) by supporting poor farmers in Africa. Charity A supports the farmers by investing in their infrastructure (water, electricity, roads, etc.), which indirectly help all farmers. Charity B provides support directly to the farmers in the form of unconditional cash transfers.
H83: Infrastructures > direct unconditional cash transfers (<50)
AnalyzeComparison(data, "A73_2allocation", "Infrastructures vs. direct unconditional cash transfers", 50)##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -4.194184 92.00000 0.0000630 -12.58065 Cohen's d -0.4349167 -0.6465445 -0.2211275
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 93 37.41935 40.00000 28.92656 2.999545
## ────────────────────────────────────────────────────────────────────────────
Direct vs indirect unconditional cash transfers (H84)
Charities A and B both help those identified and verified as being in need in Africa using unconditional cash transfers. Charity A transfers money to recipients using cash money handed by a local charity representative. Charity B transfers money directly to recipients through mobile phone money transfers (supported by all mobile phones in their region, and all recipients already have mobile phones and stable mobile connectivity).
H84: Indirect > direct unconditional cash transfers (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 0.2533880 105.0000 0.8004639 0.7547170 Cohen's d 0.02461121 -0.1658450 0.2149503
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 106 50.75472 50.00000 30.66557 2.978504
## ─────────────────────────────────────────────────────────────────────────────
Based in US vs. foreign (H85r)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A was founded at and is based in a foreign country. Charity B was founded at and is based in your home country.
H85: Ingroup > Outgroup (>50) (Reverse) Recoded to H85r: Ingroup > Outgroup (<50)
(Note: Reversed item from pre-registration, to align with other ingroup-outgroup comparisons)
data$A75_2allocation_recorded <- 100 - data$A75_2allocation
AnalyzeComparison(data, "A75_2allocation_recorded", "Based in US vs. foreign", 50)##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -6.312667 102.0000 < .0000001 -14.85437 Cohen's d -0.6220055 -0.8318191 -0.4096179
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 103 35.14563 40.00000 23.88141 2.353105
## ─────────────────────────────────────────────────────────────────────────────
Experts vs RCTs (H86)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A bases their interventions on the recommendations of a think-tank of leading experts in the field. Charity B bases their interventions on the latest scientific information using Randomized Controlled Trials.
H86: Experts > RCTs (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 2.315602 118.0000 0.0223072 5.042017 Cohen's d 0.2122709 0.03013618 0.3935265
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 119 55.04202 50.00000 23.75275 2.177411
## ─────────────────────────────────────────────────────────────────────────────
Sharing on each donation vs. aggregate (H87)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). Charity A provides detailed information regarding how each and every donation helped their cause. Charity B provides aggregated statistical summaries of the impact of all donations combined.
H87: Sharing on each donation > aggregate (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -5.203880 117.0000 0.0000008 -11.01695 Cohen's d -0.4790560 -0.6686981 -0.2875714
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 118 38.98305 50.00000 22.99721 2.117064
## ─────────────────────────────────────────────────────────────────────────────
Proportion 2: Specific communities (H88)
Charities A and B both aim to save lives in specific communities. Charity A focuses on a community of 100,000 and for each $1,000 can help 1,000 of the 100,000. Charity B focuses on a community of 1,000,000 (1 million) and for each $1,000 can help 1,000 of the 1,000,000. Imagine that you have $10,000 to allocate between the two charities.
H88: High proportion (Smaller camp) > Low proportion (Larger camp) (<50)
(Note: see also H26, we kept them both)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -2.291746 91.00000 0.0242274 -5.434783 Cohen's d -0.2389311 -0.4455533 -0.03103331
## ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 92 44.56522 50.00000 22.74624 2.371459
## ────────────────────────────────────────────────────────────────────────────
Short vs. long term (H89)
Charities A and B both save the same number of people who lack access to sufficient food. Per each $1,000 spent, Charity A provides relief for 5 people who are currently experiencing food shortage. Per each $1,000 spent, Charity B can ensure that overall 5 fewer people who would face food shortages in the long term.
H89: Long term > Short term (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -1.850514 122.0000 0.0666586 -3.658537 Cohen's d -0.1668552 -0.3444754 0.01143914
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 123 46.34146 50.00000 21.92642 1.977038
## ─────────────────────────────────────────────────────────────────────────────
Membership (ingroup) (H90)
Charities A and B both save lives with the same effectiveness (lives saved per dollar spent). You are registered as a member in Charity A. You are not registered as a member in Charity B.
H90: Member > Not a member (<50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t -11.26781 111.0000 < .0000001 -24.19643 Cohen's d -1.064708 -1.295235 -0.8310464
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ─────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ─────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 112 25.80357 20.00000 22.72588 2.147394
## ─────────────────────────────────────────────────────────────────────────────
Advocating personal responsibility (H91)
Charities A and B have the same effectiveness in addressing the cause of global warming. Charity A emphasizes that fighting global warming is your own personal responsibility. Charity B does not address the topic of personal responsibility.
H91: Not advocating personal responsibility > Advocating personal responsibility (>50)
##
## ONE SAMPLE T-TEST
##
## One Sample T-Test
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Statistic df p Mean difference Effect Size Lower Upper
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. Student's t 0.4239403 90.00000 0.6726209 1.318681 Cohen's d 0.04444102 -0.1612421 0.2498806
## ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Note. Hₐ μ ≠ 50
##
##
## Descriptives
## ────────────────────────────────────────────────────────────────────────────
## N Mean Median SD SE
## ────────────────────────────────────────────────────────────────────────────
## dataset..VarName.. 91 51.31868 50.00000 29.67261 3.110535
## ────────────────────────────────────────────────────────────────────────────
Exploratoy grouping (CAUTION)
CAUTION: Given that participants answered 23 out of 104 items, trying to do comparisons between the singular scenarios results in very small Ns, and not powered enough, this is added here for demonstration purposes only. DO NOT USE.
(Exploratory: Not pre-registered) Added comparisons and grouping between the individual scenarios, after some groups pointed out links between the different scenarios.
Ingroup-outgroup: Comparing H27, H66, H82, H85r
#
# jmv::anovaRM(
# data = data,
# rm = list(
# list(
# label="Ingroup-outgroup",
# levels=c(
# "US vs. Africa",
# "US region vs. not in region",
# "Local US community vs. Africa",
# "Based in US vs. foreign"))),
# rmCells = list(
# list(
# measure="A17_2allocation",
# cell="US vs. Africa"),
# list(
# measure="A56_2allocation",
# cell="US region vs. not in region"),
# list(
# measure="A72_2allocation",
# cell="Local US community vs. Africa"),
# list(
# measure="A75_2allocation_recorded",
# cell="Based in US vs. foreign")),
# effectSize = c("eta", "partEta"),
# depLabel = "% allocation to B",
# rmTerms = ~ `Ingroup-outgroup`,
# postHoc = list(
# "Ingroup-outgroup"),
# emMeans = ~ `Ingroup-outgroup`,
# emmTables = TRUE,
# emmPlotData = TRUE,
# groupSumm = TRUE)
# data_ingroup <- data.frame(data$A17_2allocation,
# data$A56_2allocation,
# data$A72_2allocation,
# data$A75_2allocation_recorded)
# colnames(data_ingroup) <- c("US vs. Africa",
# "US region vs. not in region",
# "Local US community vs. Africa",
# "Based in US vs. foreign")
# data_ingroup_mod <- melt(data_ingroup)
# data_ingroup_mod <- data.frame(data_ingroup_mod)
# data_ingroup_mod <- na.omit(data_ingroup_mod)
# data_ingroup_mod <- remove_labels(data_ingroup_mod)
#
# ggwithinstats(
# data = data_ingroup_mod,
# x = variable,
# y = value,
# xlab = "US (local) vs. Not US",
# ylab = "% allocation to B",
# plot.type = "boxviolin",
# title = "Ingroup-outgroup: Comparing all conditions",
# point.args = list(size = 3, alpha = 0.2, position =
# ggplot2::position_jitterdodge(jitter.width = 0.4,
# jitter.height = 3)),
# ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
# type = "parametric"
# )Approach
# jmv::anovaRM(
# data = data,
# rm = list(
# list(
# label="Approach",
# levels=c(
# "Treatment vs. Preventive",
# "Immediate relief vs. root causes",
# "Remedy vs. Preventive"))),
# rmCells = list(
# list(
# measure="A4_2allocation",
# cell="Treatment vs. Preventive"),
# list(
# measure="A21_2allocation",
# cell="Immediate relief vs. root causes"),
# list(
# measure="A54_2allocation_recoded",
# cell="Remedy vs. Preventive")),
# effectSize = c("eta", "partEta"),
# depLabel = "% allocation to B",
# rmTerms = ~ Approach,
# postHoc = list(
# "Approach"),
# emMeans = ~ Approach,
# emmTables = TRUE,
# emmPlotData = TRUE,
# groupSumm = TRUE)
# data_approach <- data.frame(data$A4_2allocation,
# data$A21_2allocation,
# data$A54_2allocation_recoded)
# colnames(data_approach) <- c("Treatment vs. Preventive",
# "Immediate relief vs. root causes",
# "Remedy vs. Preventive")
# data_approach_mod <- melt(data_approach)
# data_approach_mod <- data.frame(data_approach_mod)
# data_approach_mod <- na.omit(data_approach_mod)
# data_approach_mod <- remove_labels(data_approach_mod)
#
# ggwithinstats(
# data = data_approach_mod,
# x = variable,
# y = value,
# xlab = "Approach",
# ylab = "% allocation to B",
# plot.type = "boxviolin",
# title = "Approach: Comparing all conditions",
# point.args = list(size = 3, alpha = 0.2, position =
# ggplot2::position_jitterdodge(jitter.width = 0.4,
# jitter.height = 3)),
# ggplot.component = ggplot2::scale_y_continuous(breaks = seq(0,100,10)),
# type = "parametric"
# )Others to be combined in future data collection
Group: Shared beliefs 1 (H36) Shared beliefs 2 (H37)
INFO: Environment and packages used
## [1] "R version:"## [1] "R version 4.2.1 (2022-06-23 ucrt)"## [1] "Rstudio version:"## [1] '2023.6.0.421'## [1] "Citations for packages used:"## Package Version Citation
## 1 base 4.2.1 @base
## 2 DataExplorer 0.8.2 @DataExplorer
## 3 jmv 2.3.4 @jmv
## 4 knitr 1.43 @knitr2014; @knitr2015; @knitr2023
## 5 rmarkdown 2.23 @rmarkdown2018; @rmarkdown2020; @rmarkdown2023
## 6 rmdformats 1.0.4 @rmdformats
## 7 tidyverse 2.0.0 @tidyverse