Original Article

Estimation of the predictive power of the model in mixed-effects meta-regression: A simulation study

  1. José Antonio López-López1,
  2. Fulgencio Marín-Martínez1,*,
  3. Julio Sánchez-Meca1,
  4. Wim Van den Noortgate2,
  5. Wolfgang Viechtbauer3

Article first published online: 8 JAN 2013

DOI: 10.1111/bmsp.12002

Issue

Cover image for Vol. 66 Issue 2

British Journal of Mathematical and Statistical Psychology

Early View (Online Version of Record published before inclusion in an issue)

Additional Information

How to Cite

López-López, J. A., Marín-Martínez, F., Sánchez-Meca, J., Van den Noortgate, W. and Viechtbauer, W. (2013), Estimation of the predictive power of the model in mixed-effects meta-regression: A simulation study. British Journal of Mathematical and Statistical Psychology. doi: 10.1111/bmsp.12002

Author Information

  1. 1

    Dept. Basic Psychology & Methodology, University of Murcia, Spain

  2. 2

    University of Leuven, Belgium

  3. 3

    Maastricht University, The Netherlands

*Correspondence should be addressed to Fulgencio Marín-Martínez, Ph. D., Assistant Professor of Methodology of the Behavioral Sciences, Dept. Basic Psychology & Methodology, Faculty of Psychology, Espinardo Campus, University of Murcia, 30100-Murcia, Spain (e-mail: fulmarin@um.es).

Publication History

  1. Article first published online: 8 JAN 2013
  2. Manuscript Accepted: 7 NOV 2012
  3. Manuscript Revised: 2 NOV 2012
  4. Manuscript Received: 31 JUL 2012

Funded by

  • Fundación Séneca

SEARCH

SEARCH BY CITATION

ARTICLE TOOLS

View Full Article (HTML) Get PDF (294K)

Several methods are available to estimate the total and residual amount of heterogeneity in meta-analysis, leading to different alternatives when estimating the predictive power in mixed-effects meta-regression models using the formula proposed by Raudenbush (1994, 2009). In this paper, a simulation study was conducted to compare the performance of seven estimators of these parameters under various realistic scenarios in psychology and related fields. Our results suggest that the number of studies (k) exerts the most important influence on the accuracy of the results, and that precise estimates of the heterogeneity variances and the model predictive power can only be expected with at least 20 and 40 studies, respectively. Increases in the average within-study sample size (inline image) also improved the results for all estimators. Some differences among the accuracy of the estimators were observed, especially under adverse (small k and inline image) conditions, while the results for the different methods tended to convergence for more optimal scenarios.

View Full Article (HTML) Get PDF (294K)