load("TIPI.RData")
# fit an mlm
tipi.mlm <- lm(cbind(Extraversion, Neuroticism, Conscientiousness, Agreeableness, Openness)
~ engnat + gender + education, data = TIPI )
Anova(tipi.mlm)
heplot(tipi.mlm, fill=TRUE, fill.alpha=0.1)
pairs(tipi.mlm, fill=TRUE, fill.alpha=0.1)
# candisc works best for factors with >2 levels
tipi.can <- candisc(tipi.mlm, term="education")
tipi.can
plot(tipi.can, ellipse = TRUE)
heplot(tipi.can, fill=TRUE, fill.alpha=0.1,
var.col = "darkred", var.cex = 1.5, var.lwd = 3)
# do it for all terms
tipi.canL <- candiscList(tipi.mlm)
tipi.canL
op <- par(mfrow=c(2,2))
plot(tipi.canL, ask = FALSE)
par(op)
plot(tipi.canL$engnat)
plot(tipi.canL$gender)
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