[R-meta] robust variance estimator in meta-analyses of rare events (proportions)
@c @ending from imbi@uni-freiburg@de
Thu Oct 4 17:18:59 CEST 2018
Am 04.10.18 um 15:50 schrieb Pier-Alexandre Tardif:
> Dear Guido,
> Yes I already tried this method (I replicated http://www.metafor-project.org/doku.php/analyses:stijnen2010), results were slightly different from that obtained using the previous classic code but it's hard to tell which is more or less biased given the many differences involved!?
For rare binary data, I would postulate that GLMMs taking the binary
structure into account are more appropriate than classic methods
assuming normality of the transformed proportions within individual studies.
> Moreover, for a meta-analysis of proportions we can only use the logit transformation with rma.glmm (double arcsine is not available) and I still wouldn't know how to get the back-transformed values if I use a robust variance estimator (e.g. with clubSandwich package). Any ideas from here?
I see no problem in using the logit transformation. Futhermore, I do not
think that using a robust variance estimator is necessary if you are
using GLMMs. Maybe somebody else could comment on this.
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