A comparison of procedures to test for moderators in mixed-effects meta-regression models

Psychol Methods. 2015 Sep;20(3):360-74. doi: 10.1037/met0000023. Epub 2014 Aug 11.


Several alternative methods are available when testing for moderators in mixed-effects meta-regression models. A simulation study was carried out to compare different methods in terms of their Type I error and statistical power rates. We included the standard (Wald-type) test, the method proposed by Knapp and Hartung (2003) in 2 different versions, the Huber-White method, the likelihood ratio test, and the permutation test in the simulation study. These methods were combined with 7 estimators for the amount of residual heterogeneity in the effect sizes. Our results show that the standard method, applied in most meta-analyses up to date, does not control the Type I error rate adequately, sometimes leading to overly conservative, but usually to inflated, Type I error rates. Of the different methods evaluated, only the Knapp and Hartung method and the permutation test provide adequate control of the Type I error rate across all conditions. Due to its computational simplicity, the Knapp and Hartung method is recommended as a suitable option for most meta-analyses.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Interpretation, Statistical*
  • Humans
  • Meta-Analysis as Topic*
  • Regression Analysis*