[R-meta] Simple Bayesian meta-analysis in R

Gaspar Lukacs g@@p@r@|uk@c@ @end|ng |rom un|v|e@@c@@t
Fri Sep 27 17:44:49 CEST 2019


I'd like to conduct a Bayesian meta-analysis in R in order to support
equivalence between the effects of two design types (within each study).
E.g., Bayes factors would be perfect.

The metaBMA package seems to imply that I can get simple Bayes factors for
a moderator in a meta-analysis. (Most other Bayesian packages don't seem to
allow moderators.) But I don't find any info about how exactly to use it
and/or how to interpret the output.

Here is a simple example:

bayes_model = metaBMA::meta_random(
    y = cohens_d~version,
    SE = sed,
    labels = study,
    data = met_bf

"cohens_d" is the effect in each study, separately for each of the two
levels of "version", and I would simply want to know whether there is
substantial support for the equivalence between the "version" factors. Is
this model correct? And in any case, how can I get Bayes factors out of it
(or any direct proof of equivalence)?

A more detailed description of the question is here (where I was suggested
this mailing list):

I'd much appreciate any help.


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