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Cited by 274

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Correct Confidence Intervals for Various Regression Effect Sizes and Parameters: The Importance of Noncentral Distributions in Computing Intervals

Smithson, Michael·2001·Educational and Psychological Measurement

Abstract

The advantages that confidence intervals have over null-hypothesis significance testing have been presented on many occasions to researchers in psychology. This article provides a practical introduction to methods of constructing confidence intervals for multiple and partial R 2 and related parameters in multiple regression models based on “noncentral” F and χ 2 distributions. Until recently, these techniques have not been widely available due to their neglect in popular statistical textbooks and software. These difficulties are addressed here via freely available SPSS scripts and software and illustrations of their use. The article concludes with discussions of implications for the interpretation of findings in terms of noncentral confidence intervals, alternative measures of effect size, the relationship between noncentral confidence intervals and power analysis, and the design of studies.

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Metadata

Authors
Smithson, M.
Venue
Educational and Psychological Measurement
Published
2001-08
Volume
61
Issue
4
Pages
605-632
ISSN
  • 0013-1644 (ISSN-L)
  • 1552-3888
OpenAlex
W2065026925
Cited by
274
References
2
FWCI
12.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Correct Confidence Intervals for Various Regression Effect Sizes and Parameters: The Importance of Noncentral Distributions in Computing Intervals. https://app.cochat.ai/papers/10.1177/00131640121971392
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Smithson, M. (2001). Correct Confidence Intervals for Various Regression Effect Sizes and Parameters: The Importance of Noncentral Distributions in Computing Intervals. Educational and Psychological Measurement. https://doi.org/10.1177/00131640121971392

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.