metacum: Cumulative meta-analysis

Description

Performs a cumulative meta-analysis.

Usage

metacum(x, pooled, sortvar, level=x$level, level.comb=x$level.comb)

Arguments

An object of class meta.

pooled

A character string indicating whether a fixed effect or random effects model is used for pooling. Either missing (see Details), "fixed", or "random", can be abbreviated.

sortvar

An optional vector used to sort the individual studies (must be of same length as x$TE).

level

The level used to calculate confidence intervals for individual studies.

level.comb

The level used to calculate confidence intervals for pooled estimates.

Value

An object of class c("metacum", "meta") with corresponding print, plot function. The object is a list containing the following components:
TE, seTEEstimated treatment effect and standard error of pooled estimate in cumulative meta-analyses.
studlabStudy label describing addition of studies.
p.valueP-value for test of overall effect.
I2Heterogeneity statistic I2.
tauSquare-root of between-study variance.
smSummary measure.
methodMethod used for pooling.
kNumber of studies combined in meta-analysis.
pooledAs defined above.
TE.fixed, seTE.fixedValue is NA.
TE.random, seTE.randomValue is NA.
QValue is NA.
tauValue is NA.
levelThe level used to calculate confidence intervals for individual studies.
level.combThe level used to calculate confidence intervals for pooled estimates.

Details

A cumulative meta-analysis is performed. Studies are included sequentially as defined by sortvar.

Information from object x is utilised if argument pooled is missing. A fixed effect model is assumed (pooled="fixed") if parameter x$comb.fixed is TRUE; a random effects model is assumed (pooled="random") if parameter x$comb.random is TRUE and x$comb.fixed is FALSE.

References

Cooper H & Hedges LV (1994), The Handbook of Research Synthesis. Newbury Park, CA: Russell Sage Foundation.

Examples

Run this code

data(Fleiss93)
meta1 <- metabin(event.e, n.e, event.c, n.c,
                 data=Fleiss93, studlab=study,
                 sm="RR", meth="I")
meta1

metacum(meta1)
metacum(meta1, pooled="random")

grid.newpage()
forest(metacum(meta1, pooled="random"))

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