Combining independent estimators in research synthesis

Abstract

Extensive research literatures in the social sciences have led some research reviewers to the use of quantitative methods for research synthesis. The methods used most frequently involve estimation of a standardized mean difference (Glass's effect size). Reviewers frequently wish to examine the relationship between study characteristics (experimental conditions) and effect size. This paper presents asymptotic theory for the analysis of linear models for effect sizes. These procedures can be used to obtain efficient estimates of effect size, fit linear models to effect size data and test model specification.