MockJury | R Documentation |
Male participants were shown a picture of one of three young women. Pilot work had indicated that the one woman was beautiful, another of average physical attractiveness, and the third unattractive. Participants rated the woman they saw on each of twelve attributes. These measures were used to check on the manipulation by the photo.
A data frame with 114 observations on the following 17 variables.
Attr
Attractiveness of the photo, a factor with levels Beautiful
Average
Unattractive
Crime
Type of crime, a factor with levels Burglary
(theft of items from victim's room) Swindle
(conned a male victim)
Years
length of sentence given the defendant by the mock juror subject
Serious
a rating of how serious the subject thought the defendant's crime was
exciting
rating of the photo for 'exciting'
calm
rating of the photo for 'calm'
independent
rating of the photo for 'independent'
sincere
rating of the photo for 'sincere'
warm
rating of the photo for 'warm'
phyattr
rating of the photo for 'physical attractiveness'
sociable
rating of the photo for 'exciting'
kind
rating of the photo for 'kind'
intelligent
rating of the photo for 'intelligent'
strong
rating of the photo for 'strong'
sophisticated
rating of the photo for 'sophisticated'
happy
rating of the photo for 'happy'
ownPA
self-rating of the subject for 'physical attractiveness'
Then the participants were told that the person in the photo had committed a Crime, and asked to rate the seriousness of the crime and recommend a prison sentence, in Years.
Does attractiveness of the "defendant" influence the sentence or perceived seriousness of the crime? Does attractiveness interact with the nature of the crime?
Originally obtained from Dr. Wuensch's StatData page, https://core.ecu.edu/wuenschk/StatData/PLASTER.dat
Data from the thesis by Plaster, M. E. (1989). Inmates as mock jurors: The effects of physical attractiveness upon juridic decisions. M.A. thesis, Greenville, NC: East Carolina University.
# manipulation check: test ratings of the photos classified by Attractiveness
jury.mod1 <- lm( cbind(phyattr, happy, independent, sophisticated) ~ Attr, data=MockJury)
car::Anova(jury.mod1, test="Roy")
heplot(jury.mod1, main="HE plot for manipulation check")
pairs(jury.mod1)
if (require(candisc)) {
jury.can <- candisc(jury.mod1)
jury.can
heplot(jury.can, main="Canonical HE plot")
}
# influence of Attr of photo and nature of crime on Serious and Years
jury.mod2 <- lm( cbind(Serious, Years) ~ Attr * Crime, data=MockJury)
car::Anova(jury.mod2, test="Roy")
heplot(jury.mod2)
# stepdown test (ANCOVA), controlling for Serious
jury.mod3 <- lm( Years ~ Serious + Attr * Crime, data=MockJury)
car::Anova(jury.mod3)
# need to consider heterogeneous slopes?
jury.mod4 <- lm( Years ~ Serious * Attr * Crime, data=MockJury)
car::Anova(jury.mod3, jury.mod4)
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