![]() An additional test, due to Breslow and Day (1980), is provided with the odds ratio meta-analysis. 2003): Q is included in each StatsDirect meta-analysis function because it forms part of the DerSimonian-Laird random effects pooling method DerSimonian and Laird 1985). Conversely, Q has too much power as a test of heterogeneity if the number of studies is large ( Higgins et al. Q has low power as a comprehensive test of heterogeneity ( Gavaghan et al, 2000), especially when the number of studies is small, i.e. Q is distributed as a chi-square statistic with k (numer of studies) minus 1 degrees of freedom. The classical measure of heterogeneity is Cochran’s Q, which is calculated as the weighted sum of squared differences between individual study effects and the pooled effect across studies, with the weights being those used in the pooling method. Measuring the inconsistency of studies’ results StatsDirect calls statistics for measuring heterogentiy in meta-analysis 'non-combinability' statistics in order to help the user to interpret the results. Heterogeneity in meta-analysis refers to the variation in study outcomes between studies.
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