Bayesian meta-analysis of corrected effect sizes
Hello! I apologize if this seems dumb but I haven't seen it addressed.
I am new to Bayesian meta-analysis. While I find it very insightful, I am looking to expand its power to re-examine previous meta-analyses. Because the Bayesian meta-analytic modeling itself is comparatively recent, its literature basis is sparse.
My question is, what do JASP gurus and the blog community members think about conducting a Bayesian meta-analysis on effect sizes that have been corrected for measurement error (a.k.a. low reliability) and other artifacts such as restriction of range?
Based on other posts, I understand that JASP does not have a weighting function for effect sizes. That's fine. My question is about the feasibility and interpretability of a Bayesian meta-analysis of corrected effect sizes -- i.e. corrected in the JASP data input sheet, then analyzed with a Bayesian model in JASP.
Thank you!
Ted.
Comments
I've asked our expert. In general, I prefer to do a Bayesian analysis in one step; that is, include the weighting and the meta-analysis simultaneously. But the two-step approach (weighting first, then Bayesian model) may be a reasonable approximation. This may be relevant: https://online.ucpress.edu/collabra/article/3/1/25/112377/Bayesian-Inference-for-Correlations-in-the
EJ
thank you!