[R-meta] Intuitive explanation of BLUPs

[Dr. Gerta Rücker]

Hi Emily,

What you observe in a meta-analysis are the random means (or whatever effect measure is used) of the chosen endpoint in each study. If your model is the random effects model, this means that these observations randomly deviate in one or the other direction from the true means in each study. The random effects model provides an estimate of tau^2, the variance of the means between the studies. Moreover, using the tau estimate, it allows estimating the true expectations for each study. These are called BLUPs.

Best,
Gerta


-----Ursprüngliche Nachricht-----
Von: R-sig-meta-analysis <r-sig-meta-analysis-bounces using r-project.org> Im Auftrag von Emily Russell via R-sig-meta-analysis
Gesendet: Donnerstag, 15. Februar 2024 09:35
An: r-sig-meta-analysis using r-project.org
Cc: Emily Russell <emilyrussell99 using outlook.com>
Betreff: [R-meta] Intuitive explanation of BLUPs

Dear All

Sorry if this question is too simple, but could anyone give me an intuitive explanation of best linear unbiased prediction (BLUP) applied to meta-analysis?  Everything I can find seems to refer to genes, and I can't quite make the connection to meta-analysis.

Thanks

Emily

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