Revision 18b6abd7720cf34e0f34e4c63478dfca33bacea6 authored by Bendix Carstensen on 10 January 2007, 00:00:00 UTC, committed by Gabor Csardi on 10 January 2007, 00:00:00 UTC
1 parent b69dff2
ccwc.Rd
\name{ccwc}
\alias{ccwc}
\title{Generate a nested case-control study}
\usage{
ccwc(entry=0, exit, fail, origin=0, controls=1, match=list(), include=list(), data=NULL, silent=F)
}
\arguments{
\item{entry}{
Time of entry to follow-up
}
\item{exit}{
Time of exit from follow-up
}
\item{fail}{
Status on exit (1=Fail, 0=Censored)
}
\item{origin}{
Origin of analysis time scale
}
\item{controls}{
The number of controls to be selected for each case
}
\item{match}{
List of categorical variables on which to match cases and controls
}
\item{include}{
List of other variables to be carried across into the case-control
study
}
\item{data}{
Data frame in which to look for input variables
}
\item{silent}{
If False, echos a . to the screen for each case-control set
created; otherwise produces no output.
}
}
\description{
Given the basic outcome variables for a cohort study: the time of entry
to the cohort, the time of exit and the reason for exit ("failure" or
"censoring"), this function computes risk sets and generates a matched
case-control study in which each case is compared with a set of controls
randomly sampled from the appropriate risk set. Other variables may be
matched when selecting controls.
}
\value{
The case-control study, as a dataframe containing:
\item{Set}{
case-control set number
}
\item{Map}{
row number of record in input dataframe
}
\item{Time}{
failure time of the case in this set
}
\item{Fail}{
failure status (1=case, 0=control)
}
These are followed by the matching variables, and finally by the
variables in the \code{include} list
}
\references{
Clayton and Hills, Statistical Models in Epidemiology, Oxford
University Press, Oxford:1993.
}
\author{
David Clayton
}
\seealso{
\code{\link{Lexis}}
}
\examples{
#
# For the diet and heart dataset, create a nested case-control study
# using the age scale and matching on job
#
data(diet)
dietcc <- ccwc(doe, dox, chd, origin=dob, controls=2, data=diet,
include=energy, match=job)
}
\keyword{datagen}
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