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.
Keywords
Confidence intervalStatisticsMeta-analysisStrictly standardized mean differenceHomogeneity (statistics)Sample size determinationMathematicsCoverage probabilityCredible intervalRobust confidence intervalsRandom effects modelEconometricsMedicine
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Publication Info
- Year
- 2009
- Type
- article
- Volume
- 14
- Issue
- 3
- Pages
- 225-238
- Citations
- 123
- Access
- Closed
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Cite This
Douglas G. Bonett
(2009).
Meta-analytic interval estimation for standardized and unstandardized mean differences..
Psychological Methods
, 14
(3)
, 225-238.
https://doi.org/10.1037/a0016619
Identifiers
- DOI
- 10.1037/a0016619