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Moderator effects differ on alternative effect-size measures.

Michael Smithson1, Yiyun Shou2

  • 1Research School of Psychology, The Australian National University, Bldg 39, Canberra, ACT, 2601, Australia. michael.smithson@gmail.com.

Behavior Research Methods
|May 1, 2016
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Summary
This summary is machine-generated.

Popular effect-size measures in ANOVA and regression can yield contradictory moderation results. This study identifies when this occurs and offers solutions for reliable research reporting and meta-analysis.

Keywords:
ANOVACohen’s dEffect sizeModeratorPartial correlationRegressionRegression coefficientReplicationSemi-partial correlation

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Area of Science:

  • Statistics
  • Psychometrics
  • Quantitative Psychology

Background:

  • Moderation analysis is crucial for understanding effect-size variations.
  • Commonly used effect-size measures may exhibit inconsistent moderation patterns.
  • Discrepancies in moderation can impact research interpretation.

Purpose of the Study:

  • To highlight the issue of differential moderation of effect-size measures.
  • To identify conditions leading to inconsistent moderation results.
  • To provide methods for addressing these inconsistencies in statistical analyses.

Main Methods:

  • Examined effect-size measures in ANOVA and multiple regression.
  • Simulated conditions where differential moderation is likely.
  • Reviewed statistical techniques for detecting and managing moderation discrepancies.

Main Results:

  • Popular effect-size measures are not always moderated identically across samples.
  • Inconsistent moderation can lead to contradictory or opposite conclusions.
  • Differential moderation occurs under common analytical conditions.

Conclusions:

  • Researchers must be aware of potential discrepancies in effect-size moderation.
  • Careful selection and reporting of effect-size measures are essential.
  • Addressing differential moderation improves research integrity, replication, and meta-analysis accuracy.