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library(car) # for OBrienKaiser data
## OBK.R HE plots for repeated measures designs, OBrienKaiser data
# simplified analysis of OBrienKaiser data, collapsing over hour
OBK <- OBrienKaiser
OBK$pre <- rowMeans(OBK[,3:7])
OBK$post <- rowMeans(OBK[,8:12])
OBK$fup <- rowMeans(OBK[,13:17])
# remove separate hour scores
OBK <- OBK[,-(3:17)]
#contrasts(OBK$treatment) <- matrix(c(-2, 1, 1, 0, -1, 1), ncol=2)
# MANOVA model
mod.OBK <- lm(cbind(pre, post, fup) ~ treatment*gender, data=OBK)
# for linear and quadratic effects of 'Time'
session <- ordered(c("pretest", "posttest", "followup"),
levels=c("pretest", "posttest", "followup"))
# for profile contrasts
contrasts(session) <- matrix(c(-1, 1, 0,
0, -1, 1), ncol=2)
#colnames(contrasts(session)) <- c("Post-Pre", "Fol-Post")
idata <- data.frame(session)
# Multivariate tests for repeated measures
aov.OBK <- Manova(mod.OBK, idata=idata, idesign=~session, type="III")
aov.OBK
# Univariate tests for repeated measures
summary(aov.OBK, multivariate=FALSE)
# HE plots for Between-S effects
heplot(mod.OBK, hypotheses=c("treatment1", "treatment2"),
col=c("red", "black", "blue", "brown", "gray", "gray"),
hyp.labels=c("(A,B)-Control", "A-B"),
main="Between-S effects: Treat*Gender"
)
pairs(mod.OBK, col=c("red", "black", "blue", "brown"))
if(requireNamespace("rgl")){
heplot3d(mod.OBK, hypotheses=c("treatment1", "treatment2"),
col=c("pink", "black", "blue", "green3", "gray40", "gray40"),
hyp.labels=c("(A,B)-Control", "A-B"))
}
# HE plots for Within-S effects
heplot(mod.OBK, idata=idata, idesign=~session, iterm="session",
main="Within-S effects: Session: (Treat*Gender)")
### Plotting the Within-S effects by 'manually' transforming Y -> Y M
# Transform to profile contrasts for within-S effects
OBK$session.1 <- OBK$post - OBK$pre
OBK$session.2 <- OBK$fup - OBK$post
mod1.OBK <- lm(cbind(session.1, session.2) ~ treatment*gender, data=OBK)
# HE plots for Within-S effects
heplot(mod1.OBK,
main="Within-S effects: Session * (Treat*Gender)",
remove.intercept=FALSE, type="III",
xlab="Post-Pre", ylab="Fup-Post",
term.labels=c("session", "treatment:session", "gender:session",
"treatment:gender:session"),
col=c("red", "black", "blue", "brown"),
xlim=c(-2,4), ylim=c(-2,3)
)
mark.H0()
# Main effect of session tests H0: Intercept=0
mod2.OBK <- lm(cbind(session.1, session.2) ~ 1, data=OBK)
heplot(mod2.OBK,
terms="(Intercept)", col=c("red", "blue"), type="3",
# remove.intercept=FALSE,
main="Within-S effects (profile contrasts): session",
xlab="Post-Pre", ylab="Fup-Post",
term.labels="session",
xlim=c(-2,4), ylim=c(-2,3)
)
mark.H0()
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