[R-meta] robust variance estimator in meta-analyses of rare events (proportions)

Pier-Alexandre Tardif pier-@lex@ndre@t@rdif@1 @ending from ul@v@l@c@
Thu Oct 4 15:50:10 CEST 2018

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!? 

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?



-----Message d'origine-----
De : R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] De la part de Guido Schwarzer
Envoyé : 4 octobre 2018 08:33
À : r-sig-meta-analysis using r-project.org
Objet : Re: [R-meta] robust variance estimator in meta-analyses of rare events (proportions)


You only provided R code to conduct a classic meta-analysis using inverse variance weights.

Instead of using the inverse variance method, Stijnen et al. (2010) - part of your reference list - suggest to use generalized linear mixed models for meta-analysis of proportions; see section 3.1.

This method is available in R packages metafor (R function rma.glmm) and meta (R function metaprop calling internally rma.glmm from metafor).

Best wishes,

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