metagen {meta} | R Documentation |
Fixed and random effects meta-analysis based on estimates and their standard errors; inverse variance weighting is used for pooling.
metagen(TE, seTE, studlab, data=NULL, subset=NULL, sm="", level = 0.95, level.comb = level)
TE |
Estimate of treatment effect. |
seTE |
Standard error of treatment estimate. |
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. |
sm |
A character string indicating underlying summary measure,
e.g., "RD" , "RR" , "OR" , "AS" ,
"MD" , "SMD" . |
level |
The level used to calculate confidence intervals for individual studies. |
level.comb |
The level used to calculate confidence intervals for pooled estimates. |
Generic method for meta-analysis, only treatment estimates and their standard error are needed. The method is useful, e.g., for pooling of log hazard ratios. The inverse variance method is used for pooling. Random effects estimate is based on the DerSimonian-Laird method.
An object of class c("metagen", "meta")
with corresponding
print
, summary
, plot
function. The object is a
list containing the following components:
TE, seTE, studlab, |
As defined above. |
sm |
|
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" . |
level |
The level used to calculate confidence intervals for individual studies. |
level.comb |
The level used to calculate confidence intervals for pooled estimates. |
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(Fleiss93) meta1 <- metabin(event.e, n.e, event.c, n.c, data=Fleiss93, sm="RR", meth="I") meta1 ## ## Identical results by using the following commands: ## meta1 metagen(meta1$TE, meta1$seTE, sm="RR")