While pooling eight homogeneous trials of similar populations, interventions and outcome definitions into a meta-analysis, which model assumes that all included studies share one single true underlying effect size, and that differences between study estimates arise purely from chance?

• A Random effects model
• B Fixed effects model ✓
• C Weighted least squares regression model
• D Bayesian hierarchical model

Explanation

The fixed effects model posits a single common true effect shared by all studies, attributing between-study variation in observed estimates to sampling error alone, and weights studies by inverse variance. The random effects model instead assumes the true effect varies across studies and incorporates between-study variance (Tau squared) into the weights, widening confidence intervals. It becomes appropriate when heterogeneity is substantial. Weighted regression and Bayesian hierarchical models are not the conventional default choices described in this setting.

Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.

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