heplots (version 1.2-0)

MockJury: Effects Of Physical Attractiveness Upon Mock Jury Decisions

Description

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. 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 "defendent" influence the sentence or perceived seriousness of the crime? Does attractiveness interact with the nature of the crime?

Usage

data(MockJury)

source

From Dr. Wuensch's StatData Page, http://core.ecu.edu/psyc/wuenschk/StatData/PLASTER.dat

References

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.

Examples

# manipulation check:  test ratings of the photos classified by Attractiveness
jury.mod1 <- lm( cbind(phyattr, happy, independent, sophisticated) ~ Attr, data=MockJury)
Anova(jury.mod1, test="Roy")
## 
## Type II MANOVA Tests: Roy test statistic
##      Df test stat approx F num Df den Df    Pr(>F)    
## Attr  2    1.7672   48.156      4    109 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

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)
Anova(jury.mod2, test="Roy")
heplot(jury.mod2)

# stepdown test (ANCOVA), controlling for Serious
jury.mod3 <- lm( Years ~ Serious + Attr * Crime, data=MockJury)
Anova(jury.mod3)

# need to consider heterogeneous slopes?
jury.mod4 <- lm( Years ~ Serious * Attr * Crime, data=MockJury)
anova(jury.mod3, jury.mod4)