[R-meta] Should I fit both the only-intercept and the meta-regression?
luca.santini.eco at gmail.com
Tue Mar 20 08:28:56 CET 2018
I’m totally new to meta-analytical approaches, I am running my first meta-analysis using "metafor" but I am now a bit confused about the interpretation.
I am running 2 mixed-effect meta-analyses (only-intercept models) on correlation coefficients (models A and B). I have an hypothesis for a possible continuous moderator for both of the mixed-effect models.
When I run the meta-analyses without the moderator, the intercept of model A is significant and supports the hypothesis. When I run the meta-analyses with the moderator (metaregressions), both the intercept and the moderator coefficients of model B are significant, whereas neither of the coefficients of model A are significant.
In other words, my conclusions change if I use the simple mixed-effect meta-analysis, or the mixed-effect meta-analyis with the moderator (metaregression).
So my question is,
- should I run both of them and use only-intercept model to test my hypothesis and the metaregression just as a test for the moderator variable?
- should I only run the metaregression and interpret both the intercept and the moderator coefficient?
- should I run the meta-regression directly but only retain moderators if supported by information criteria (AIC, BIC, DIC or similar?)
Note that if I apply the third option using AIC, the moderator of model A is excluded whereas the moderator of model B is retained, resulting in both models being significant.
I found both cases in the literature, authors that use the simple meta-analysis and separately the metaregression to test the effect of moderators and authors that only run the metaregression, so I’m a bit confused.
Would you be so kind to share your expert opinion on this? Thanks in advance.
[[alternative HTML version deleted]]
More information about the R-sig-meta-analysis