Nonparametric estimators of effect size in meta-analysis

Larry V. Hedges*, Ingram Olkin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

86 Scopus citations

Abstract

When observations are normally distributed, the sample standardized mean difference is a consistent and asymptotically efficient estimator of effect size in meta-analysis. However, in some cases the observations are far from normally distributed, and a nonparametric index of effect magnitude is desirable. The logic of the estimator proposed by H. C. Kraemer and G. Andrews (see record 1982-11171-001) is extended to provide related nonparametric estimators of different parameters that may be appropriate under other experimental conditions. (21 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).

Original languageEnglish (US)
Pages (from-to)573-580
Number of pages8
JournalPsychological Bulletin
Volume96
Issue number3
DOIs
StatePublished - Nov 1 1984

Keywords

  • nonparametric effect size estimation in meta analysis

ASJC Scopus subject areas

  • Psychology(all)

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