https://github.com/cran/metafor
Tip revision: 65608550671a8644a98c94812b6dffe5bfa64cba authored by Wolfgang Viechtbauer on 29 April 2014, 00:00:00 UTC
version 1.9-3
version 1.9-3
Tip revision: 6560855
dat.collins1985a.Rd
\name{dat.collins1985a}
\docType{data}
\alias{dat.collins1985a}
\title{Studies on the Treatment of Upper Gastrointestinal Bleeding by a Histamine H2 Antagonist}
\description{Results from studies examining the presence of persistent or recurrent bleedings in patients receiving either a histamine H2 antagonist or placebo.}
\usage{dat.collins1985a}
\format{The data frame contains the following columns:
\tabular{lll}{
\bold{id} \tab \code{numeric} \tab study number \cr
\bold{ref} \tab \code{numeric} \tab reference number \cr
\bold{year} \tab \code{numeric} \tab year of publication \cr
\bold{nti} \tab \code{numeric} \tab number of patients in treatment group \cr
\bold{xti} \tab \code{numeric} \tab number of patients in treatment group with persistent or recurrent bleedings \cr
\bold{nci} \tab \code{numeric} \tab number of patients in placebo group \cr
\bold{xci} \tab \code{numeric} \tab number of patients in placebo group with persistent or recurrent bleedings
}
}
\details{
The data in this dataset were obtained from Table I in van Houwelingen, Zwinderman, and Stijnen (1993).
}
\source{
van Houwelingen, H. C., Zwinderman, K. H., & Stijnen, T. (1993). A bivariate approach to meta-analysis. \emph{Statistics in Medicine}, \bold{12}, 2273--2284.
}
\references{
Collins, R., & Langman, M. (1985). Treatment with histamine H2 antagonists in acute upper gastrointestinal hemorrhage. \emph{New England Journal of Medicine}, \bold{313}, 660--666.
}
\examples{
### load data
dat <- get(data(dat.collins1985a))
### calculate (log) odds ratio and sampling variance
dat <- escalc(measure="OR", ai=xci, n1i=nci, ci=xti, n2i=nti, data=dat, to="all")
summary(dat, digits=2, transf=exp)
### meta-analysis of log odds ratios using Peto's method
res <- rma.peto(ai=xci, n1i=nci, ci=xti, n2i=nti, data=dat)
summary(res)
\dontrun{
### meta-analysis of log odds ratios using conditional logistic regression model
res <- rma.glmm(measure="OR", ai=xci, n1i=nci, ci=xti, n2i=nti, data=dat,
model="CM.EL", method="FE")
summary(res)
### plot the log-likelihoods of the odds ratios
llplot(measure="OR", ai=xci, n1i=nci, ci=xti, n2i=nti, data=dat,
lwd=1, refline=NA, xlim=c(-4,4), drop00=FALSE)
### meta-analysis of log odds ratios using conditional logistic regression model
res <- rma.glmm(measure="OR", ai=xci, n1i=nci, ci=xti, n2i=nti, data=dat,
model="CM.EL", method="ML")
summary(res)
}
}
\keyword{datasets}