Message-ID: <7d2a311e-3029-9b07-a718-842bd462e909@imbi.uni-freiburg.de>
Date: 2020-01-09T18:31:13Z
From: Guido Schwarzer
Subject: [R-meta] Subgroup analysis output using metafor - interpretation
In-Reply-To: <CAF8zgfZJHr0Y0U_v_Cn0uTwP4ofVCUMEHEBgynbvFR+uc0ApkA@mail.gmail.com>
Am 09.01.20 um 15:26 schrieb Joao Afonso:
> [...]
> As for the outliers I could take a step back and instead of removing them
> leave them in the data-set and see what happens when conducting the
> sub-group analysis. Is this best practice when conducing a meta-analysis?
I am no expert on outlier detection (in meta-analysis), however, I would
say that it is in general a good idea to try to explain between-study
heterogeneity using subgroup analysis or meta-regression first.
An intrinsic feature / problem of the meta-analysis of prevalences is
typically the substantial between-study heterogeneity (which is clearly
visible in your meta-analysis with an I2 of 99.7%). In my view, the main
aim of a prevalence meta-analysis is actually to describe this
heterogeneity. Removing outliers would reduce this heterogeneity and
paint a different picture. I assume that there will be still substantial
heterogeneity after conducting subgroup analyses. Prediction intervals
can help to properly describe the between-study heterogeneity.
Best wishes, Guido