Message-ID: <f565cf4d1a214e1285a79f1a55c98a9d@UM-MAIL3214.unimaas.nl>
Date: 2022-09-19T08:58:06Z
From: Wolfgang Viechtbauer
Subject: [R-meta] Selection models for rma.mv-objects
In-Reply-To: <3f5bd18b295d489aa8f0624cb04d05ac@uni-trier.de>
Dear Therese,
Implementing selection models for multilevel/multivariate models is very difficult, because it might involve the repeated computation of multiple integrals (while the selection models for 'rma.uni' objects involve repeated computation of simple integrals, which is already numerically challenging). Hence, as far as I know, nobody has implemented selection models for multilevel/multivariate models.
This aside, for multilevel/multivariate models, one also has to carefully consider where/how selection may have taken place. For the individual effect sizes? Or for entire studies altogether? Or a combination of the two? For modeling selection of entire studies, the question is also what the selection depends on. The p-value of the most significant effect size? Or the p-value of what might have been the focal effect size within a study? Or the p-value of some kind of omnibus test of multiple effect sizes?
At the moment, I would say the regression test is the most straightforward technique that generalizes and that one could use for multilevel/multivariate models. See also:
https://doi.org/10.1037/met0000300
The paper also examines a selection model, but it wasn't clear to me whether this was some kind of multivariate version of it or not. Maybe James (or Melissa - but I am not sure if she is subscribed to this mailing list) can comment on this.
Best,
Wolfgang
>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On
>Behalf Of Th?lking, Theresa
>Sent: Monday, 19 September, 2022 10:22
>To: r-sig-meta-analysis at r-project.org
>Subject: [R-meta] Selection models for rma.mv-objects
>
>Hello everybody,
>
>is there a function available in R that enables selection models for rma.mv-
>objects? I could only find an implementation for rma.uni.
>
>Thanks in advance.
>
>Best,
>Theresa