\Header{infert}{Infertility after Spontaneous and Induced Abortion}
\keyword{datasets}{infert}
\begin{Description}\relax
This is a matched case-control study dating from before the
availability of conditional logistic regression.\end{Description}
\begin{Usage}
\begin{verbatim}data(infert)\end{verbatim}
\end{Usage}
\begin{Format}\relax
\Tabular{rll}{
1.  & Education  & 0 = 0-5  years \\
&            & 1 = 6-11 years \\
&            & 2 = 12+  years  \\
2.  & age        & age in years of case \\
3.  & parity     & count \\
4.  & number of prior & 0 = 0 \\
& induced abortions & 1 = 1 \\
&            & 2 = 2 or more \\
5.  & case status& 1 = case \\
&            & 0 = control \\
6.  & number of prior & 0 = 0 \\
& spontaneous abortions & 1 = 1 \\
&            & 2 = 2 or more \\
7.  & matched set number & 1-83 \\
8.  & stratum number & 1-63}\end{Format}
\begin{Note}\relax
One case with two prior spontaneous abortions and two prior induced
abortions is omitted.\end{Note}
\begin{Source}\relax
Trichopoulos et al. (1976)
\emph{Br. J. of Obst. and Gynaec.} \bold{83}, 645--650.\end{Source}
\begin{Examples}
\begin{ExampleCode}
data(infert)
model1 <- glm(case ~ spontaneous+induced, data=infert,family=binomial())
summary(model1)
## adjusted for other potential confounders:
summary(model2 <- glm(case ~ age+parity+education+spontaneous+induced,
                data=infert,family=binomial()))
## Really should be analysed by conditional logistic regression
## which is equivalent to a Cox model :
if(require(survival5)){
  faketime <- rep(42,nrow(infert))
  model3 <- coxph(Surv(faketime,case)~spontaneous+induced+strata(stratum),
                data=infert,method="exact")
  summary(model3)
  detach()# survival5 (conflicts)
}
\end{ExampleCode}
\end{Examples}

