rm(list = ls())
tense <- read.table(
url("http://stat.unm.edu/~fletcher/LLM/DATA/Example3-7-1.DAT"),
#"C:\\E-drive\\Books\\ANREG2\\newdata\\tab20-10a.dat",
#"C:\\E-drive\\Books\\LOGLIN3\\DATA\\Example3-7-1.dat",
		  sep="",col.names=c("y","Tn","Wt","Ms","Dr"))
attach(tense)
tense
#summary(tense)

W=factor(Wt)
M=factor(Ms)
D=factor(Dr)
T=factor(Tn)
m7 <- glm(y ~ T:W:M+T:W:D+T:M:D+W:M:D,family = poisson)
m4 <- glm(y ~ T:W+T:M+T:D+W:M+W:D+M:D,family = poisson)
m0 <- glm(y ~ T + W + M + D,family = poisson)

df=c(m7$df.residual,m4$df.residual,m0$df.residual)
G2=c(m7$deviance,m4$deviance,m0$deviance)
A2q=G2-(2*df)
modelm=c(df,G2,A2q)
model=matrix(modelm,3,3,
      dimnames=list(NULL,c("df","G2","A-q")))
model
\end{verbatim}


You can also get the key statistics from the following commands
\\[.1in] \textbf{Code}~\thesection.2.\begin{verbatim}
m7 <- glm(y ~ T*W*M+T*W*D+T*M*D+W*M*D,family=poisson)
m7p=summary(m7)
m7p
anova(m7)