[R-meta] rma.glmm model selection

[Viechtbauer, Wolfgang (SP)]

Hi Philippe,

Good question. I doubt that a direct comparison of the likelihoods of these models (or information criteria) is meaningful though. For example, UM.FS and UM.RS differ both in terms of their fixed and random effects (since the whole point is to use either fixed or random study effects). CM.AL and CM.EL differ even more fundamentally, as they use other distributions.

The sentence that you quote is true, but the devil is, as always, in the details. Here, I was thinking more in terms of: We have some specific model where we can swap in or out certain random effects. Once you start swapping in and out fixed and random effects at the same time and even switching distributions, then things get a lot more tricky.

So, I really don't have any good suggestions at the moment.

Best,
Wolfgang

>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On
>Behalf Of Philippe Tadger
>Sent: Saturday, 11 September, 2021 12:42
>To: r-sig-meta-analysis using r-project.org
>Subject: [R-meta] rma.glmm model selection
>
>Dear Meta community
>
>I would like to ask for guidance on  how to do model selection in
>metafor::rma.glmm. I'm thinking specifically in the comparison between:
>UM.FS, UM.RS, CM.AL, CM.EL methods. Is it possible to conduct a goodness
>of fit or alternative selection methods between the 4 models?
>
>I saw the model selection here
>https://www.metafor-
>project.org/doku.php/tips:model_selection_with_glmulti_and_mumin
><https://www.metafor-
>project.org/doku.php/tips:model_selection_with_glmulti_and_mumin>
>for predictors that mention that is possible to do a similar approach
>with rma.glmm. Also a specific phrase catch my attention: "one can also
>consider model selection with respect to the random effects structure."
>
>Thanks in advance for your help and time
>
>--
>
>Kind regards/Saludos cordiales
>*Philippe Tadger*
>ORCID <https://orcid.org/0000-0002-1453-4105>, Reseach Gate
><https://www.researchgate.net/profile/Philippe-Tadger>
>Phone/WhatsApp: +32498774742