, Volume 60, Issue 3, pp 419–435 | Cite as

A general linear model for estimating effect size in the presence of publication bias

  • Jack L. Vevea
  • Larry V. Hedges


When the process of publication favors studies with smallp-values, and hence large effect estimates, combined estimates from many studies may be biased. This paper describes a model for estimation of effect size when there is selection based on one-tailedp-values. The model employs the method of maximum likelihood in the context of a mixed (fixed and random) effects general linear model for effect sizes. It offers a test for the presence of publication bias, and corrected estimates of the parameters of the linear model for effect magnitude. The model is illustrated using a well-known data set on the benefits of psychotherapy.

Key words

meta-analysis research synthesis publication bias effect size mixed models selection models 


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Copyright information

© The Psychometric Society 1995

Authors and Affiliations

  • Jack L. Vevea
    • 1
  • Larry V. Hedges
    • 1
  1. 1.University of ChicagoUSA

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