Extract Various Types of Variance-Covariance Matrices from 'rma' Objects
The function extracts various types of variance-covariance matrices from objects of class "rma"
. By default, the variance-covariance matrix of the parameter estimates (fixed effects) is returned.
## S3 method for class 'rma' vcov(object, type="fixed", ...)
object |
an object of class |
type |
character string indicating the type of variance-covariance matrix to return; |
... |
other arguments. |
Note that type="obs"
currently only works for object of class "rma.uni"
and "rma.mv"
.
For objects of class "rma.uni"
, the marginal variance-covariance matrix is just a diagonal matrix with τ² + vᵢ along the diagonal, where τ² is the estimated amount of (residual) heterogeneity (set to 0 in fixed-effects models) and vᵢ is the sampling variance of the ith study.
For objects of class "rma.mv"
, the structure can be more complex and depends on the types of random effects included in the model.
A matrix corresponding to the requested variance-covariance matrix.
Wolfgang Viechtbauer wvb@metafor-project.org http://www.metafor-project.org/
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://www.jstatsoft.org/v036/i03.
### meta-analysis of the log risk ratios using a mixed-effects model ### with two moderators (absolute latitude and publication year) res <- rma(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, mods = ~ ablat + year, data=dat.bcg) vcov(res) ### marginal var-cov matrix of the observed log risk ratios vcov(res, type="obs") ### var-cov matrix of the fitted values vcov(res, type="fitted") ### var-cov matrix of the residuals vcov(res, type="resid")
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