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Testing overall and moderator effects in random effects meta‐regression

Hilde M. Huizenga, Ingmar Visser, Conor V. Dolan

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Source: Crossref

Published: Jan 25, 2011

DOI: 10.1348/000711010x522687

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Source abstract

Random effects meta‐regression is a technique to synthesize results of multiple studies. It allows for a test of an overall effect, as well as for tests of effects of study characteristics, that is, (discrete or continuous) moderator effects. We describe various procedures to test moderator effects: the z , t , likelihood ratio (LR), Bartlett‐corrected LR (BcLR), and resampling tests. We compare the Type I error of these tests, and conclude that the common z test, and to a lesser extent the LR test, do not perform well since they may yield Type I error rates appreciably larger than the chosen alpha. The error rate of the resampling test is accurate, closely followed by the BcLR test. The error rate of the t test is less accurate but arguably tolerable. With respect to statistical power, the BcLR and t tests slightly outperform the resampling test. Therefore, our recommendation is to use either the resampling or the BcLR test. If these statistics are unavailable, then the t test should be used since it is certainly superior to the z test.

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Testing overall and moderator effects in random effects meta‐regression — Mathematical Frontier Network