title: Testing overall and moderator effects in random effects meta-regression.
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.
authors.affiliation: Department of Psychology, University of Amsterdam, The Netherlands. h.m.huizenga@uva.nl
authors.forename: Hilde M
authors.initials: HM
authors.lastname: Huizenga
authors.forename: Ingmar
authors.initials: I
authors.lastname: Visser
authors.forename: Conor V
authors.initials: CV
authors.lastname: Dolan
mesh_terms: D000374:Aggression / Q000523:psychology*; D001521:Behavior Therapy / Q000706:statistics & numerical data; D002648:Child; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D003198:Computer Simulation; D003625:Data Collection / Q000706:statistics & numerical data; D015987:Effect Modifier, Epidemiologic; D006801:Humans; D016013:Likelihood Functions; D015201:Meta-Analysis as Topic; D009010:Monte Carlo Method; D012044:Regression Analysis; D012107:Research Design / Q000706:statistics & numerical data; D012959:Socioeconomic Factors