An academic guide to read a forest plot in a meta-analysis, including how to verify effect direction, scale, labels, confidence intervals, study weights, pooled estimates, subgroups, heterogeneity, and prediction intervals in.
An academic guide to fixed-effect vs random-effects meta-analysis, including how to document common-effect or random-effects assumptions, estimator, confidence-interval method, heterogeneity handling, sensitivity plans, software.
An academic guide to choose an effect size for meta-analysis, including how to document the outcome type, construct, measurement scale, direction, candidate effect measure, compatibility assumptions, software output, and rationale.
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