https://github.com/cran/BayesDA
Tip revision: bffdc42c3f8912d3bef31ee5fbd0b1092fcbd906 authored by Kjetil Halvorsen on 20 February 2008, 00:00:00 UTC
version 1.0-1
version 1.0-1
Tip revision: bffdc42
meta.Rd
\name{meta}
\alias{meta}
\docType{data}
\title{ Results of 22 Clinical Trials of beta-Blockers }
\description{
Results of 22 clinical trials of beta-blockers for reducing mortality
after myocardial infection. Used for meta-analysis.
}
\usage{data(meta)}
\format{
A data frame with 22 observations on the following 5 variables.
\describe{
\item{\code{study}}{id code of study}
\item{\code{control.deaths}}{number of deaths in control group}
\item{\code{control.total}}{total number of patients in control group}
\item{\code{treated.deaths}}{number of deaths in treatment group}
\item{\code{treated.total}}{total number of patients in treatment group}
}
}
\details{
The 22 clinical trials each consist of two groups of heart attack patients
randomly allocated to receive or not receive beta-blockers ( a family of
drugs
that affect the central nervous system and can relax the
heart musckles).
}
\source{
}
\references{
}
\examples{
data(meta)
names(meta)
# Calculating empirical log-odds and its sampling variances:
y <- apply(meta, 1, function(x) log( (x[4]/(x[5]-x[4]))/(x[2]/(x[3]-x[2])) ) )
s2 <- apply(meta, 1, function(x) 1/(x[5]-x[4]) + 1/x[4] +1/(x[3]-x[2]) + 1/x[2] )
cbind("Study number"=meta[,1], "empirical log odds"=y, "empirical sampling variance of y"=s2)
#if(require(meta)){
# funnel(y, sqrt(s2))
# radial(y, sqrt(s2))
#}
}
\keyword{datasets}
\concept{meta analysis}