\HeaderA{esoph}{Smoking, Alcohol and (O)esophageal Cancer}{esoph}
\keyword{datasets}{esoph}
\begin{Description}\relax
Data from a case-control study of (o)esophageal cancer in
Ile-et-Vilaine, France.
\end{Description}
\begin{Usage}
\begin{verbatim}esoph\end{verbatim}
\end{Usage}
\begin{Format}\relax
A data frame with records for 88 age/alcohol/tobacco combinations.

\Tabular{rlll}{
[,1] & "agegp" & Age group & 1  25--34 years\\
& & & 2  35--44\\
& & & 3  45--54\\
& & & 4  55--64\\
& & & 5  65--74\\
& & & 6  75+\\{}
[,2] & "alcgp" & Alcohol consumption & 1   0--39 gm/day\\
& & & 2  40--79\\
& & & 3  80--119\\
& & & 4  120+\\{}
[,3] & "tobgp" & Tobacco consumption & 1   0-- 9 gm/day\\
& & & 2  10--19\\
& & & 3  20--29\\
& & & 4  30+\\{}
[,4] & "ncases" & Number of cases & \\{}
[,5] & "ncontrols" & Number of controls &
}
\end{Format}
\begin{Author}\relax
Thomas Lumley
\end{Author}
\begin{Source}\relax
Breslow, N. E. and Day, N. E. (1980)
\emph{Statistical Methods in Cancer Research. 1: The Analysis of
Case-Control Studies.}  IARC Lyon / Oxford University Press.
\end{Source}
\begin{Examples}
\begin{ExampleCode}
require(stats)
require(graphics) # for mosaicplot
summary(esoph)
## effects of alcohol, tobacco and interaction, age-adjusted
model1 <- glm(cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp,
              data = esoph, family = binomial())
anova(model1)
## Try a linear effect of alcohol and tobacco
model2 <- glm(cbind(ncases, ncontrols) ~ agegp + unclass(tobgp)
                                         + unclass(alcgp),
              data = esoph, family = binomial())
summary(model2)
## Re-arrange data for a mosaic plot
ttt <- table(esoph$agegp, esoph$alcgp, esoph$tobgp)
ttt[ttt == 1] <- esoph$ncases
tt1 <- table(esoph$agegp, esoph$alcgp, esoph$tobgp)
tt1[tt1 == 1] <- esoph$ncontrols
tt <- array(c(ttt, tt1), c(dim(ttt),2),
            c(dimnames(ttt), list(c("Cancer", "control"))))
mosaicplot(tt, main = "esoph data set", color = TRUE)
\end{ExampleCode}
\end{Examples}

