metacum function

Cumulative meta-analysis

Performs a cumulative meta-analysis.

## S3 method for class 'meta'
metacum(x, pooled, sortvar, no = 1, ...)

metacum(x, ...)

## Default S3 method:
metacum(x, ...)

Arguments

• x: An object of class meta.
• pooled: A character string indicating whether a common effect or random effects model is used for pooling. Either missing (see Details), "common", or "random", can be abbreviated.
• sortvar: An optional vector used to sort the individual studies (must be of same length as x$TE).
• no: A numeric specifying which meta-analysis results to consider.
• ...: Additional arguments (ignored).

Returns

An object of class "meta" and "metacum" with corresponding generic functions (see meta-object).

The following list elements have a different meaning: - TE, seTE: Estimated treatment effect and standard error of pooled estimate in cumulative meta-analyses.

• lower, upper: Lower and upper confidence interval limits.

• statistic: Statistic for test of overall effect.

• pval: P-value for test of overall effect.

• studlab: Study label describing addition of studies.

• w: Sum of weights from common effect or random effects model.

• TE.common, seTE.common: Value is NA.

• TE.random, seTE.random: Value is NA.

• Q: Value is NA.

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 common effect model is assumed (pooled = "common") if argument x$common is TRUE; a random effects model is assumed (pooled = "random") if argument x$random is TRUE and x$common is FALSE.

Examples

data(Fleiss1993bin)
m1 <- metabin(d.asp, n.asp, d.plac, n.plac,
  data = Fleiss1993bin, studlab = study, sm = "RR", method = "I")
m1
metacum(m1)
metacum(m1, pooled = "random")

forest(metacum(m1))
forest(metacum(m1, pooled = "random"))

metacum(m1, sortvar = study)
metacum(m1, sortvar = 7:1)

m2 <- update(m1, title = "Fleiss1993bin meta-analysis", backtransf = FALSE)
metacum(m2)

data(Fleiss1993cont)
m3 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
  data = Fleiss1993cont, sm = "SMD")
metacum(m3)

References

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

See Also

metabin, metacont, print.meta

Author(s)

Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de