Description:

This Master Prompt would focus on the core statistical synthesis of effect sizes across studies. It would guide researchers through study weighting, inverse-variance methods, fixed-effect versus random-effects models, estimation of pooled effects, confidence intervals, prediction intervals and appropriate interpretation of forest plots.

Particular attention would be given to the assumptions underlying alternative pooling models rather than selecting a random-effects model automatically. Researchers would be guided to interpret the magnitude, direction, precision and practical importance of pooled effects instead of relying exclusively on p-values. Random-effects synthesis and forest-plot interpretation are strongly represented throughout the uploaded literature.