In a meta-analysis, the funnel plot of individual study effect estimates against their standard errors shows clear asymmetry, with smaller studies clustered to one side of the pooled estimate. The most likely explanation is:

• A Random error alone, requiring no further evaluation
• B Correct application of a fixed-effects model
• C Excessive statistical power in the included trials
• D Publication bias or small-study effects, with smaller negative studies remaining unpublished ✓

Explanation

In the absence of bias, studies scatter symmetrically around the pooled estimate, with imprecision increasing as standard error grows. Asymmetry suggests smaller positive studies were published while smaller null or opposing studies were suppressed, producing publication bias and inflating the pooled effect. Statistical power does not create asymmetry, and model choice affects weighting, not the shape of the plot. Formal tests such as Egger's regression can quantify the asymmetry.

Reference: Systematic Reviews in Health Care: Meta-analysis in Context (Egger, Davey Smith, Altman), 2nd ed.

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