Meta-analysis has become an important supplement to traditional methods of research reviewing, although many problems must be addressed by the reviewer who carries out a meta-analysis. These problems include identifying and obtaining appropriate studies, extracting estimates of effect size from the studies, coding or classifying studies, analyzing the data, and reporting the results of the data analysis. Earlier work by Glass, McGaw, and Smith describes methods for dealing with these problems: and has generated a great interest in the development of systematic statistical theory for meta-analysis. This monograph supplements the existing literature on meta-analysis by providing a unified treatment of rigorous statistical methods for meta-analysis. These methods provide a mechanism for responding to criticisms of meta-analysis, such as that meta-analysis may lead to oversimplified conclusions or be influenced by design flaws in the original research studies. Contents include: indices of effect size, statistical analysis of effect size data, assumptions and the statistical model, estimations of effect size, an analogue to the analysis of variance for effect sizes, the effects of measurement error on effect size, statistical analysis when correlations or proportions are the index of effect magnitude, and statistical analysis for correlations as effect magnitude. (Author/PN)