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. An alternative test statistic is presented and a better approximating test distribution is derived. Explicitely discussed are the methods in the unbalanced heteroscedastic 1-way random ANOVA model and for the probability difference method, including interaction treatment by centres. Numerical results are presented by simulation studies.