rm(list = ls())
chap.mlr <- read.table(
url("http://stat.unm.edu/~fletcher/LLM/DATA/CHAPMAN.DAT"),
#"C:\\E-drive\\Books\\ANREG2\\newdata\\chapman.dat",
#"C:\\E-drive\\Books\\LOGLIN3\\DATA\\chapman.dat",
sep="",col.names=
c("Case","Ag","S","D","Ch","H","W","y"))

attach(chap.mlr)
chap.mlr
#summary(chap.mlr)

#Summary tables
cm <- glm(y ~ Ag+Ch+W,family = binomial)
cmp=summary(cm)
cmp
#anova(cm)

# Diagnostics
rpearson=(y-cm$fit)/(cm$fit*(1-cm$fit))^(.5)
rstand=rpearson/(1-hatvalues(cm))^(.5)
infv = c(y,cm$fit,hatvalues(cm),rpearson,
		  rstand,cooks.distance(cm))
inf=matrix(infv,I(cmp$df[1]+cmp$df[2]),6,dimnames =
list(NULL,c("y","phat","lev","Pearson","Stand.","C")))
inf