\Header{bacteria}{Presence of Bacteria after Drug Treatments}
\keyword{datasets}{bacteria}
\begin{Description}\relax
Tests of the presence of the bacteria
\emph{H. influenzae}
in children with otitis media in the Northern Territory of Australia.
\end{Description}
\begin{Usage}
\begin{verbatim}
data(bacteria)
\end{verbatim}
\end{Usage}
\begin{Format}\relax
This data frame has 220 rows and the following columns:
\describe{
\item[y] presence or absence: a factor with levels
\code{n} and \code{y}.
\item[ap] active/placebo: a factor with levels \code{a} and \code{p}.
\item[hilo] hi/low compliance: a factor with levels \code{hi} amd
\code{lo}.
\item[week] numeric: week of test.
\item[ID] subject ID: a factor.
\item[trt] a factor with levels \code{placebo}, \code{drug} and
\code{drug+}, a re-coding of \code{ap} and \code{hilo}.
}
\end{Format}
\begin{Details}\relax
Dr A. Leach tested the effects of a drug on 50 children with a history of
otitis media in the Northern Territory of Australia.  The children
were randomized to the drug or the a placebo, and also to receive
active encouragement to comply with taking the drug.

The presence of
\emph{H. influenzae}
was checked at weeks 0, 2, 4, 6
and 11: 30 of the checks were missing and are not included in this
data frame.
\end{Details}
\begin{Source}\relax
Menzies School of Health Research 1999--2000 Annual Report pp. 18--21
(\url{http://www.menzies.edu.au/publications/anreps/MSHR00.pdf}).
\end{Source}
\begin{References}\relax
Venables, W. N. and Ripley, B. D. (2002)
\emph{Modern Applied Statistics with S.} Fourth edition.  Springer.
\end{References}
\begin{Examples}
\begin{ExampleCode}
contrasts(bacteria$trt) <- structure(contr.sdif(3),
     dimnames = list(NULL, c("drug", "encourage")))
## fixed effects analyses
summary(glm(y ~ trt * week, binomial, data = bacteria))
summary(glm(y ~ trt + week, binomial, data = bacteria))
summary(glm(y ~ trt + I(week > 2), binomial, data = bacteria))

# conditional random-effects analysis
library(survival)
bacteria$Time <- rep(1, nrow(bacteria))
coxph(Surv(Time, unclass(y)) ~ week + strata(ID),
      data = bacteria, method = "exact")
coxph(Surv(Time, unclass(y)) ~ factor(week) + strata(ID),
      data = bacteria, method = "exact")
coxph(Surv(Time, unclass(y)) ~ I(week > 2) + strata(ID),
      data = bacteria, method = "exact")

# PQL glmm analysis
library(nlme)
summary(glmmPQL(y ~ trt + I(week > 2), random = ~ 1 | ID,
                family = binomial, data = bacteria))
\end{ExampleCode}
\end{Examples}

