https://github.com/cran/meta
Tip revision: db0ba742ea8cc3b6b369d22f18e6fd3b24eac8dc authored by Guido Schwarzer on 29 November 2006, 00:00:00 UTC
version 0.81
version 0.81
Tip revision: db0ba74
metabin.Rd
\name{metabin}
\alias{metabin}
\title{Meta-analysis of binary outcome data}
\description{
Calculation of fixed and random effects estimates (relative risk, odds
ratio or risk difference) for meta-analyses with binary outcome
data. Mantel-Haenszel, inverse variance and Peto method are available
for pooling.
}
\usage{
metabin(event.e, n.e, event.c, n.c, studlab,
data = NULL, subset = NULL, method = "MH",
sm = ifelse(!is.na(charmatch(method, c("Peto", "peto"), nomatch = NA)), "OR", "RR"),
incr = 0.5, allincr = FALSE, addincr = FALSE, allstudies = FALSE,
MH.exact = FALSE, RR.cochrane = FALSE, warn = TRUE)
}
\arguments{
\item{event.e}{Number of events in experimental group.}
\item{n.e}{Number of observations in experimental group.}
\item{event.c}{Number of events in control group.}
\item{n.c}{Number of observations in control group.}
\item{studlab}{An optional vector with study labels.}
\item{data}{An optional data frame containing the study information,
i.e., event.e, n.e, event.c, and n.c.}
\item{subset}{An optional vector specifying a subset of studies to be used.}
\item{method}{A character string indicating which method is to be used
for pooling of studies. One of \code{"Inverse"}, \code{"MH"}, or
\code{"Peto"}, can be abbreviated.}
\item{sm}{A character string indicating which summary measure
(\code{"RD"}, \code{"RR"}, or \code{"OR"}) is to be used for pooling
of studies.}
\item{incr}{Numerical value added to each cell frequency for studies
with a zero cell count.}
\item{allincr}{A logical indicating if \code{incr} is added to each
cell frequency of all studies if at least one study has a zero cell
count. If false, \code{incr} is added only to each cell frequency of
studies with a zero cell count.}
\item{addincr}{A logical indicating if \code{incr} is added to each cell
frequency of all studies irrespective of zero cell counts.}
\item{allstudies}{A logical indicating if studies with zero or all
events in both groups are to be included in the meta-analysis
(applies only if sm = \code{"RR"} or \code{"OR"}).}
\item{MH.exact}{A logical indicating if \code{incr} is not to be added
to all cell frequencies for studies with a zero cell count to
calculate the pooled estimate based on the Mantel-Haenszel method.}
\item{RR.cochrane}{A logical indicating if 2*\code{incr} instead of
1*\code{incr} is to be added to \code{n.e} and \code{n.c} in the
calculation of the relative risk (i.e., \code{sm="RR"}) for studies
with a zero cell. This is used in RevMan 4, the
Cochrane Collaboration's program for preparing and maintaining
Cochrane reviews.}
\item{warn}{A logical indicating whether the addition of \code{incr}
to studies with zero cell frequencies should result in a warning.}
}
\details{
Treatment estimates and standard errors are calculated for each
study. For studies with a zero cell count, by default, 0.5 is added to
all cell frequencies of these studies. Treatment estimates and
standard errors are only calculated for studies with zero or all
events in both groups if \code{allstudies} is \code{TRUE}.
Both fixed and random effects estimates are calculated. If
\code{method} is \code{"MH"} (default), the Mantel-Haenszel method is
used to calculate the fixed effects estimate; if \code{method} is
\code{"Inverse"}, inverse variance weighting is used for
pooling; finally, if \code{method} is \code{"Peto"}, the Peto method
is used for pooling. The DerSimonian-Laird estimate is used in the
random effects model.
For the Mantel-Haenszel method, by default (if \code{MH.exact} is
FALSE), 0.5 is added to all cell frequencies of a study with a zero cell
count in the calculation of the pooled estimate. This approach is also
used in other software, e.g. RevMan 4 and the Stata procedure metan.
According to Fleiss (in Cooper & Hedges, 1994), there is no need to
add 0.5 to a cell frequency of zero to calculate the Mantel-Haenszel
estimate and he advocates the exact method
(\code{MH.exact}=TRUE). Note, the estimate based on the exact method
is not defined if the number of events is zero in all studies either
in the experimental or control group.
}
\value{
An object of class \code{c("metabin", "meta")} with corresponding
\code{print}, \code{summary}, \code{plot} function. The object is a
list containing the following components:
\item{event.e, n.e, event.c, n.c, studlab,}{}
\item{sm, method, incr, allincr, addincr, }{As defined above.}
\item{allstudies, MH.exact, RR.cochrane, warn}{}
\item{TE, seTE}{Estimated treatment effect and standard error of individual studies.}
\item{w.fixed, w.random}{Weight of individual studies (in fixed and
random effects model).}
\item{TE.fixed, seTE.fixed}{Estimated overall treatment effect and
standard error (fixed effect model).}
\item{TE.random, seTE.random}{Estimated overall treatment effect and
standard error (random effects model).}
\item{k}{Number of studies combined in meta-analysis.}
\item{Q}{Heterogeneity statistic Q.}
\item{tau}{Square-root of between-study variance (moment estimator of
DerSimonian-Laird).}
\item{Q.CMH}{Cochrane-Mantel-Haenszel heterogeneity statistic.}
\item{sparse}{Logical flag indicating if any study included in
meta-analysis has any zero cell frequencies.}
\item{call}{Function call.}
}
\references{
Cooper H & Hedges LV (1994),
\emph{The Handbook of Research Synthesis}.
Newbury Park, CA: Russell Sage Foundation.
DerSimonian R & Laird N (1986),
Meta-analysis in clinical trials. \emph{Controlled Clinical Trials},
\bold{7}, 177--188.
Fleiss JL (1993),
The statistical basis of meta-analysis.
\emph{Statistical Methods in Medical Research}, \bold{2}, 121--145.
Greenland S & Robins JM (1985),
Estimation of a common effect parameter from sparse follow-up data.
\emph{Biometrics}, \bold{41}, 55--68.
\emph{Review Manager (RevMan)} [Computer program]. Version 4.2 for
Windows. Copenhagen: The Nordic Cochrane Centre, The Cochrane
Collaboration, 2003.
StataCorp. 2001.
\emph{Stata Statistical Software: Release 7.0}. College Station, TX:
Stata Corporation.
}
\author{Guido Schwarzer \email{sc@imbi.uni-freiburg.de}}
\seealso{\code{\link{funnel}}, \code{\link{metabias}}, \code{\link{metacont}}, \code{\link{metagen}}, \code{\link{print.meta}}}
\examples{
metabin(10, 20, 15, 20, sm="OR")
##
## Different results:
##
metabin(0, 10, 0, 10, sm="OR")
metabin(0, 10, 0, 10, sm="OR", allstudies=TRUE)
data(Olkin95)
meta1 <- metabin(event.e, n.e, event.c, n.c,
data=Olkin95, subset=c(41,47,51,59),
sm="RR", meth="I")
summary(meta1)
funnel(meta1)
meta2 <- metabin(event.e, n.e, event.c, n.c,
data=Olkin95, subset=Olkin95$year<1970,
sm="RR", meth="I")
summary(meta2)
}
\keyword{htest}