The R Project SVN R

\name{infert}
\title{Infertility after spontaneous and induced abortion}
\usage{data(infert)}
\alias{infert}
\format{
  \tabular{rll}{
    1.  \tab Education  \tab 0 = 0-5  years \cr
    \tab        \tab 1 = 6-11 years \cr
    \tab        \tab 2 = 12+  years  \cr
    2.  \tab age    \tab age in years of case \cr
    3.  \tab parity \tab count \cr
    4.  \tab number of prior \tab 0 = 0 \cr
    \tab induced abortions \tab 1 = 1 \cr
    \tab        \tab 2 = 2 or more \cr
    5.  \tab case status\tab 1 = case \cr
    \tab        \tab 0 = control \cr
    6.  \tab number of prior \tab 0 = 0 \cr
    \tab spontaneous abortions \tab 1 = 1 \cr
    \tab        \tab 2 = 2 or more \cr
    7.  \tab matched set number \tab 1-83 \cr
    8.  \tab stratum number \tab 1-63 \cr
  }
}
\source{Trichopoulos et al. (1976) Br. J. of Obst. and Gynaec. vol.83,
pp. 645-650.}
\description{This is a matched case-control study dating from before the
  availability of conditional logistic regression.}
\note{One case with two prior spontaneous abortions and two prior induced
  abortions is omitted.}
\examples{
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(survival4)){
  faketime <- rep(42,nrow(infert))
  model3 <- coxph(Surv(faketime,case)~spontaneous+induced+strata(stratum),
                data=infert,method="exact")
  summary(model3)
  detach()# survival4 (conflicts)
}
}
\keyword{datasets}