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We introduce a quality-effects approach that combines evidence from a series of trials comparing 2 interventions. This approach incorporates the heterogeneity of effects in the analysis of the overall interventional efficacy. However, unlike the random-effects model based on observed between-trial heterogeneity, we suggest adjustment based on measured methodological heterogeneity between studies. We propose a simple noniterative procedure for computing the combined effect size under this model and suggest that this could represent a more convincing alternative to the random effects model.