Evaluating Change in Adjusted <i>R</i> -Square and <i>R</i> -Square Indices: A Latent Variable Method Application

A procedure for interval estimation of the difference in the adjusted <i>R</i>-square index for nested linear models is discussed. The method yields as a byproduct confidence intervals for their standard <i>R</i>-square difference, as well as for the adjusted and standard <i>R</i>-squares associated with each model. The resulting interval estimate of the difference in adjusted <i>R</i>-square represents a useful and informative complement to the commonly used <i>R</i>-square change statistic and its significance test in model selection and contains substantially more information than that test. The outlined procedure is readily employed with popular software in empirical educational and psychological studies and is illustrated with numerical data.

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Publication Details

Journal
Educational and Psychological Measurement
Published
2025-04-11
DOI
https://doi.org/10.1177/00131644251329178
Primary Topic
Advanced Statistical Modeling Techniques
Type
article
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article

Evaluating Change in Adjusted R -Square and R -Square Indices: A Latent Variable Method Application

Christine DiStefano, Tenko Raykov
Educational and Psychological Measurement
Advanced Statistical Modeling Techniques
article

Evaluating Change in Adjusted R -Square and R -Square Indices: A Latent Variable Method Application

Christine DiStefano, Tenko Raykov
article en

Abstract

A procedure for interval estimation of the difference in the adjusted <i>R</i>-square index for nested linear models is discussed. The method yields as a byproduct confidence intervals for their standard <i>R</i>-square difference, as well as for the adjusted and standard <i>R</i>-squares associated with each model. The resulting interval estimate of the difference in adjusted <i>R</i>-square represents a useful and informative complement to the commonly used <i>R</i>-square change statistic and its significance test in model selection and contains substantially more information than that test. The outlined procedure is readily employed with popular software in empirical educational and psychological studies and is illustrated with numerical data.

Educational and Psychological Measurement
University of South Carolina (US), Michigan State University (US)
Openalex Percentile: Top 93%
Advanced Statistical Modeling Techniques
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