| metacont {meta} | R Documentation |
Calculation of fixed and random effects estimates for meta-analyses with continuous outcome data; inverse variance weighting is used for pooling.
metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, studlab,
data=NULL, subset=NULL, sm="MD",
level = 0.95, level.comb = level,
comb.fixed=TRUE, comb.random=TRUE,
title="", complab="", outclab="",
label.e="Experimental", label.c="Control",
byvar, bylab, print.byvar=TRUE)
n.e |
Number of observations in experimental group. |
mean.e |
Estimated mean in experimental group. |
sd.e |
Standard deviation in experimental group. |
n.c |
Number of observations in control group. |
mean.c |
Estimated mean in control group. |
sd.c |
Standard deviation in control group. |
studlab |
An optional vector with study labels. |
data |
An optional data frame containing the study information. |
subset |
An optional vector specifying a subset of studies to be used. |
level |
The level used to calculate confidence intervals for individual studies. |
level.comb |
The level used to calculate confidence intervals for pooled estimates. |
comb.fixed |
A logical indicating whether a fixed effect meta-analysis should be conducted. |
comb.random |
A logical indicating whether a random effects meta-analysis should be conducted. |
title |
Title of meta-analysis / systematic review. |
complab |
Comparison label. |
outclab |
Outcome label. |
label.e |
Label for experimental group. |
label.c |
Label for control group. |
sm |
A character string indicating which summary measure
("MD" or "SMD") is to be used for pooling of
studies. |
byvar |
An optional vector containing grouping information (must
be of same length as n.e). |
bylab |
A character string with a label for the grouping variable. |
print.byvar |
A logical indicating whether the name of the grouping variable should be printed in front of the group labels. |
Calculation of fixed and random effects estimates for meta-analyses
with continuous outcome data; inverse variance weighting is used for
pooling. The DerSimonian-Laird estimate is used in the
random effects model. The mean difference is used as measure of
treatment effect if sm="MD" – which correspond to
sm="WMD" in older versions (<0.9) of the meta package. For the
summary measure "SMD", Hedges' adjusted g is utilised for
pooling.
Internally, both fixed effect and random effects models are calculated
regardless of values choosen for arguments comb.fixed and
comb.random. Accordingly, the estimate for the random effects
model can be extracted from component TE.random of an object
of class "meta" even if comb.random=FALSE. However, all
functions in R package meta will adequately consider the values
for comb.fixed and comb.random. E.g. function
print.meta will not print results for the random effects
model if comb.random=FALSE.
The function metagen is called internally to calculate
individual and overall treatment estimates and standard errors.
An object of class c("metacont", "meta") with corresponding
print, summary, plot function. The object is a
list containing the following components:
n.e, mean.e, sd.e, |
|
n.c, mean.c, sd.c, |
|
studlab, sm, level, level.comb, |
|
comb.fixed, comb.random, |
|
byvar, bylab, print.byvar |
As defined above. |
TE, seTE |
Estimated treatment effect and standard error of individual studies. |
w.fixed, w.random |
Weight of individual studies (in fixed and random effects model). |
TE.fixed, seTE.fixed |
Estimated overall treatment effect and standard error (fixed effect model). |
TE.random, seTE.random |
Estimated overall treatment effect and standard error (random effects model). |
k |
Number of studies combined in meta-analysis. |
Q |
Heterogeneity statistic. |
tau |
Square-root of between-study variance (moment estimator of DerSimonian-Laird). |
method |
Pooling method: "Inverse". |
call |
Function call. |
Guido Schwarzer sc@imbi.uni-freiburg.de
Cooper H & Hedges LV (1994), The Handbook of Research Synthesis. Newbury Park, CA: Russell Sage Foundation.
data(Fleiss93cont)
meta1 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, data=Fleiss93cont, sm="SMD")
meta1
meta2 <- metacont(Fleiss93cont$n.e, Fleiss93cont$mean.e,
Fleiss93cont$sd.e,
Fleiss93cont$n.c, Fleiss93cont$mean.c,
Fleiss93cont$sd.c,
sm="SMD")
meta2