Which test evaluates heterogeneity in meta-analyses by determining if two or more populations have similar distributions for the same variable, with a high P value indicating homogeneity?

• A. Forest plots
• B. Funnel plots
• C. Scatter plots
• D. Line graphs

Answer: (B)

In meta-analysis, checking heterogeneity is about whether study results point to a common effect or vary beyond what chance would explain. A funnel plot helps with this by visualizing how study results distribute across different study sizes: if all studies estimate the same underlying effect, the points should form a symmetric funnel around the overall effect. A high P value in a related assessment of symmetry means there’s no statistically significant asymmetry, which supports homogeneity across populations.

Among the given options, a funnel plot is the one tied to evaluating this kind of distributional consistency in meta-analytic context. Forest plots summarize individual study estimates and the pooled result but don’t themselves test whether distributions match; scatter plots and line graphs are generic visual tools and don’t specifically address heterogeneity across study populations in meta-analysis.