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April 19, 2026Psychological Methods0 citations

Binomial effect size displays and gain-probability: Alternative ways to interpret hierarchical regression findings, with tutorial.

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DTDavid Trafimow

Key Points

  • This research aims to explore alternative interpretation methods in hierarchical regression analyses using binomial effect size and gain-probability.
  • Examined hierarchical regression paradigm with different variable entries
  • Calculated ΔR² for traditional assessments
  • Introduced binomial effect size displays and gain-probability analyses
  • Provided a tutorial for interpreting multiple correlation coefficients
  • Binomial effect size and gain-probability can yield different conclusions than traditional ΔR²
  • Multiple interpretations enhance understanding of regression findings
  • Alternative methods offer a more comprehensive view of data implications

Abstract

Researchers using a hierarchical regression paradigm enter different variables at different steps in the analysis, each time determining ΔR². Although ΔR² is traditional for both zero-order correlation coefficients and multiple correlation coefficients, it is not the only possibility. It is also possible to use binomial effect size displays and gain-probability analyses to interpret zero-order correlation coefficients. However, nobody has explored the possibility of extending these latter advances from zero-order correlation coefficients to the multiple correlation coefficients obtained in successive steps of hierarchical regression analyses. The present exposition and tutorial show that binomial effect size display and gain-probability interpretations can imply different conclusions both from each other and from ΔR². The message is not that a single interpretation should dominate but that multiple interpretations provide researchers with a more thorough and comprehensive understanding of the implications of the data. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

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Cite This Study

David Trafimow (2026) studied this question.

synapsesocial.com/papers/69e470a4010ef96374d8d920https://doi.org/10.1037/met0000839
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