Computing Correct Confidence Intervals for Anova Fixed-and Random-Effects Effect Sizes

Most textbooks explain how to compute confidence intervals for means, correlation coefficients, and other statistics using “central” test distributions (e.g., t, F) that are appropriate for such statistics. However, few textbooks explain how to use “noncentral” test distributions (e.g., noncentral t...

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Bibliographic Details
Published inEducational and psychological measurement Vol. 61; no. 4; pp. 575 - 604
Main Authors Fidler, Fiona, Thompson, Bruce
Format Journal Article
LanguageEnglish
Published Thousand Oaks, CA SAGE Publications 01.08.2001
SAGE PUBLICATIONS, INC
Subjects
Analysis of Variance
Computation
Computer Software
Confidence Intervals (Statistics)
Correlation
Effect Size
Psychology
Social sciences
Statistical analysis
Statistical Distributions
Statistical Inference
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Summary:Most textbooks explain how to compute confidence intervals for means, correlation coefficients, and other statistics using “central” test distributions (e.g., t, F) that are appropriate for such statistics. However, few textbooks explain how to use “noncentral” test distributions (e.g., noncentral t, noncentral F) to evaluate power or to compute confidence intervals for effect sizes. This article illustrates the computation of confidence intervals for effect sizes for some ANOVA applications; the use of intervals invoking noncentral distributions is made practical by newer software. Greater emphasis on both effect sizes and confidence intervals was recommended by the APA Task Force on Statistical Inference and is consistent with the editorial policies of the 17 journals that now explicitly require effect size reporting.
ISSN:0013-1644
1552-3888
DOI:10.1177/0013164401614003