Res Synth Methods - Robust variance estimation in meta-regression with binary dependent effects.

Tópicos

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Resumo

Dependent effect size estimates are a common problem in meta-analysis. Recently, a robust variance estimation method was introduced that can be used whenever effect sizes in a meta-analysis are not independent. This problem arises, for example, when effect sizes are nested or when multiple measures are collected on the same individuals. In this paper, we investigate the robustness of this method in small samples when the effect size of interest is the risk difference, log risk ratio, or log odds ratio. This simulation study examines the accuracy of 95% confidence intervals constructed using the robust variance estimator across a large variety of parameter values. We report results for both estimations of the mean effect (intercept) and of a slope. The results indicate that the robust variance estimator performs well even when the number of studies is as small as 10, although coverage is generally less than nominal in the slope estimation case. Throughout, an example based on a meta-analysis of cognitive behavior therapy is used for motivation. Copyright ? 2013 John Wiley & Sons, Ltd.

Resumo Limpo

depend effect size estim common problem metaanalysi recent robust varianc estim method introduc can use whenev effect size metaanalysi independ problem aris exampl effect size nest multipl measur collect individu paper investig robust method small sampl effect size interest risk differ log risk ratio log odd ratio simul studi examin accuraci confid interv construct use robust varianc estim across larg varieti paramet valu report result estim mean effect intercept slope result indic robust varianc estim perform well even number studi small although coverag general less nomin slope estim case throughout exampl base metaanalysi cognit behavior therapi use motiv copyright john wiley son ltd

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