An Alternative Method for Meta-Analysis

Abstract

In many fields of applications, test statistics are obtained by combining estimates from several experiments, studies or centres of a multi-centre trial. The commonly used test procedure to judge the evidence of a common overall effect can result in a considerable overestimation of the significance level, leading to a high rate of too liberal decisions. Alternative test statistics are presented and better approximating test distributions are derived. Explicitly discussed are the methods in the unbalanced heteroscedastic 1-way random ANOVA model and for the probability difference method, including interaction treatment by centres or studies. Numerical results are presented by simulation studies.

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