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A General Linear Model for Estimating Effect Size in the Presence of Publication Bias
Abstract
When the process of publication favors studies with small p-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-tailed p-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.
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Metadata
- Authors
- Vevea, J. L., & Hedges, L. V.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1995-09
- Volume
- 60
- Issue
- 3
- Pages
- 419-435
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2028854990
- Cited by
- 413
- References
- 5
- FWCI
- 2.18
- Type
- journal article
- Language
- en
- Open access
- closed
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