Meta-analytic interval estimation for standardized and unstandardized mean differences.

Abstract

The fixed-effects (FE) meta-analytic confidence intervals for unstandardized and standardized mean differences are based on an unrealistic assumption of effect-size homogeneity and perform poorly when this assumption is violated. The random-effects (RE) meta-analytic confidence intervals are based on an unrealistic assumption that the selected studies represent a random sample from a large superpopulation of studies. The RE approach cannot be justified in typical meta-analysis applications in which studies are nonrandomly selected. New FE meta-analytic confidence intervals for unstandardized and standardized mean differences are proposed that are easy to compute and perform properly under effect-size heterogeneity and nonrandomly selected studies. The proposed meta-analytic confidence intervals may be used to combine unstandardized or standardized mean differences from studies having either independent samples or dependent samples and may also be used to integrate results from previous studies into a new study. An alternative approach to assessing effect-size heterogeneity is presented.