| socsupport {DAAG} | R Documentation |
Data from a survey on social and other kinds of support.
socsupport
This data frame contains the following columns:
female, male 18-20, 21-24, 25-30,
31-40,40+ australia,
other married,
other, single alone,
friends, other, parents,
partner, residencesemployed fulltime, employed part-time,
govt assistance, other, parental supportfirst year,
other , full-time, part-timeMelissa Manning, Psychology, Australian National University
attach(socsupport) not.na <- apply(socsupport[,9:19], 1, function(x)!any(is.na(x))) ss.pr1 <- princomp(as.matrix(socsupport[not.na, 9:19]), cor=TRUE) pairs(ss.pr1$scores[,1:3]) sort(-ss.pr1$scores[,1]) # Minus the largest value appears first pause() not.na[36] <- FALSE ss.pr <- princomp(as.matrix(socsupport[not.na, 9:19]), cor=TRUE) summary(ss.pr) # Examine the contribution of the components pause() # We now regress BDI on the first six principal components: ss.lm <- lm(BDI[not.na] ~ ss.pr$scores[, 1:6], data=socsupport) summary(ss.lm)$coef pause() ss.pr$loadings[,1] plot(BDI[not.na] ~ ss.pr$scores[ ,1], col=as.numeric(gender), pch=as.numeric(gender), xlab ="1st principal component", ylab="BDI") topleft <- par()$usr[c(1,4)] legend(topleft[1], topleft[2], col=1:2, pch=1:2, legend=levels(gender))