% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/forest.metabind.R

\name{forest.metabind}

\alias{forest.metabind}

\title{Forest plot to display the result of a meta-analysis}

\usage{

\method{forest}{metabind}(

x,

leftcols,

leftlabs,

rightcols = c("effect", "ci"),

rightlabs,

common = x$common,

random = x$random,

overall = x$overall,

subgroup = FALSE,

hetstat = FALSE,

overall.hetstat = x$overall.hetstat,

prediction = x$prediction,

layout = gs("layout"),

lab.NA = "",

col.square,

col.square.lines,

col.circle,

col.circle.lines,

col.diamond,

col.diamond.common,

col.diamond.random,

col.diamond.lines,

col.diamond.lines.common,

col.diamond.lines.random,

col.predict,

col.predict.lines,

type = NULL,

type.common = NULL,

type.random = NULL,

type.predict = NULL,

digits = gs("digits.forest"),

digits.se = gs("digits.se"),

digits.stat = gs("digits.stat"),

digits.pval = max(gs("digits.pval") - 2, 2),

digits.pval.Q = max(gs("digits.pval.Q") - 2, 2),

digits.Q = gs("digits.Q"),

digits.tau2 = gs("digits.tau2"),

digits.tau = gs("digits.tau"),

digits.I2 = max(gs("digits.I2") - 1, 0),

scientific.pval = gs("scientific.pval"),

big.mark = gs("big.mark"),

print.subgroup.labels = x$with.subgroups,

addrow.subgroups = print.subgroup.labels,

smlab,

calcwidth.pooled = overall,

warn.deprecated = gs("warn.deprecated"),

...

)

}

\arguments{

\item{x}{An object of class \code{\link{metabind}}.}

\item{leftcols}{A character vector specifying (additional) columns

to be plotted on the left side of the forest plot or a logical

value (see Details).}

\item{leftlabs}{A character vector specifying labels for

(additional) columns on left side of the forest plot (see

Details).}

\item{rightcols}{A character vector specifying (additional) columns

to be plotted on the right side of the forest plot or a logical

value (see Details).}

\item{rightlabs}{A character vector specifying labels for

(additional) columns on right side of the forest plot (see

Details).}

\item{common}{A logical indicating whether common effect estimates

should be plotted.}

\item{random}{A logical indicating whether random effects estimates

should be plotted.}

\item{overall}{A logical indicating whether overall summaries

should be plotted. This argument is useful in a meta-analysis

with subgroups if summaries should only be plotted on group

level.}

\item{subgroup}{A logical indicating whether subgroup results

should be shown in forest plot. This argument is useful in a

meta-analysis with subgroups if summaries should not be plotted

on group level.}

\item{hetstat}{Either a logical value indicating whether to print

results for heterogeneity measures at all or a character string

(see Details).}

\item{overall.hetstat}{A logical value indicating whether to print

heterogeneity measures for overall treatment comparisons. This

argument is useful in a meta-analysis with subgroups if

heterogeneity statistics should only be printed on subgroup

level.}

\item{prediction}{A logical indicating whether prediction

interval(s) should be printed.}

\item{layout}{A character string specifying the layout of the

forest plot (see \code{\link{forest.meta}}).}

\item{lab.NA}{A character string to label missing values.}

\item{col.square}{The colour for squares reflecting study's weight

in the meta-analysis.}

\item{col.square.lines}{The colour for the outer lines of squares

reflecting study's weight in the meta-analysis.}

\item{col.circle}{The colour for circles reflecting study weights

in the meta-analysis.}

\item{col.circle.lines}{The colour for the outer lines of circles

reflecting study's weight in the meta-analysis.}

\item{col.diamond}{The colour of diamonds representing the results

for common effect and random effects models.}

\item{col.diamond.common}{The colour of diamonds for common effect

estimates.}

\item{col.diamond.random}{The colour of diamonds for random effects

estimates.}

\item{col.diamond.lines}{The colour of the outer lines of diamonds

representing the results for common effect and random effects

models.}

\item{col.diamond.lines.common}{The colour of the outer lines of

diamond for common effect estimates.}

\item{col.diamond.lines.random}{The colour of the outer lines of

diamond for random effects estimates.}

\item{col.predict}{Background colour of prediction intervals.}

\item{col.predict.lines}{Colour of outer lines of prediction

intervals.}

\item{type}{A character string or vector specifying how to

plot estimates.}

\item{type.common}{A single character string specifying how to

plot common effect estimates.}

\item{type.random}{A single character string specifying how to

plot random effects estimates.}

\item{type.predict}{A single character string specifying how to

plot prediction intervals.}

\item{digits}{Minimal number of significant digits for treatment

effects, see \code{print.default}.}

\item{digits.se}{Minimal number of significant digits for standard

errors, see \code{print.default}.}

\item{digits.stat}{Minimal number of significant digits for z- or

t-statistic for test of overall effect, see \code{print.default}.}

\item{digits.pval}{Minimal number of significant digits for p-value

of overall treatment effect, see \code{print.default}.}

\item{digits.pval.Q}{Minimal number of significant digits for

p-value of heterogeneity test, see \code{print.default}.}

\item{digits.Q}{Minimal number of significant digits for

heterogeneity statistic Q, see \code{print.default}.}

\item{digits.tau2}{Minimal number of significant digits for

between-study variance, see \code{print.default}.}

\item{digits.tau}{Minimal number of significant digits for square

root of between-study variance, see \code{print.default}.}

\item{digits.I2}{Minimal number of significant digits for I-squared

statistic, see \code{print.default}.}

\item{scientific.pval}{A logical specifying whether p-values should

be printed in scientific notation, e.g., 1.2345e-01 instead of

0.12345.}

\item{big.mark}{A character used as thousands separator.}

\item{print.subgroup.labels}{A logical indicating whether subgroup

label should be printed.}

\item{addrow.subgroups}{A logical value indicating whether an empty

row is printed between results for subgroups.}

\item{smlab}{A label for the summary measurex (printed at top of

figure).}

\item{calcwidth.pooled}{A logical indicating whether text for

common effect and random effects model should be considered to

calculate width of the column with study labels.}

\item{warn.deprecated}{A logical indicating whether warnings should

be printed if deprecated arguments are used.}

\item{\dots}{Additional graphical arguments (passed on to

\code{\link{forest.meta}}).}

}

\description{

Draws a forest plot in the active graphics window (using grid

graphics system).

}

\details{

A forest plot, also called confidence interval plot, is drawn in

the active graphics window. The forest functions in R package

\bold{meta} are based on the grid graphics system. In order to

print the forest plot, resize the graphics window and either use

\code{\link{dev.copy2eps}} or \code{\link{dev.copy2pdf}}. Another

possibility is to create a file using \code{\link{pdf}},

\code{\link{png}}, or \code{\link{svg}} and to specify the width

and height of the graphic (see \code{\link{forest.meta}} examples).

The arguments \code{leftcols} and \code{rightcols} can be used to

specify columns which are plotted on the left and right side of the

forest plot, respectively.

The arguments \code{leftlabs} and \code{rightlabs} can be used to

specify column headings which are plotted on left and right side of

the forest plot, respectively. For certain columns predefined

labels exist. For other columns, the column name will be used as a

label. It is possible to only provide labels for new columns (see

\code{\link{forest.meta}} examples). Otherwise the length of

\code{leftlabs} and \code{rightlabs} must be the same as the number

of printed columns, respectively. The value \code{NA} can be used

to specify columns which should use default labels.

Argument \code{hetstat} can be a character string to specify where

to print heterogeneity information:

\itemize{

\item row with results for common effect model (\code{hetstat =

"common"}),

\item row with results for random effects model (\code{hetstat =

"random"}),

\item rows with 'study' information (\code{hetstat = "study"}).

}

Otherwise, information on heterogeneity is printed in dedicated rows.

}

\examples{

data(Fleiss1993cont)

# Add some (fictitious) grouping variables:

#

Fleiss1993cont$age <- c(55, 65, 55, 65, 55)

Fleiss1993cont$region <- c("Europe", "Europe", "Asia", "Asia", "Europe")

ma <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,

data = Fleiss1993cont, sm = "SMD")

# Conduct two subgroup analyses

#

ma1 <- update(ma, subgroup = age, subgroup.name = "Age group")

ma2 <- update(ma, subgroup = region, subgroup.name = "Region")

# Combine subgroup meta-analyses and show forest plot with subgroup

# results

#

mb <- metabind(ma1, ma2)

mb

forest(mb)

}

\seealso{

\code{\link{forest.meta}}, \code{\link{metabin}},

\code{\link{metacont}}, \code{\link{metagen}},

\code{\link{metabind}}, \code{\link{settings.meta}}

}

\author{

Guido Schwarzer \email{guido.schwarzer@uniklinik-freiburg.de}

}

\keyword{hplot}