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This study enhances methods for testing moderation in repeated measures designs. It introduces new techniques for probing interactions and handling multiple moderators, simplifying complex analyses for researchers.

Keywords:
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Area of Science:

  • Psychological Science
  • Quantitative Psychology

Background:

  • Moderation hypotheses are prevalent in psychological science.
  • Existing methods for testing moderation in two-instance repeated measures designs are limited.

Purpose of the Study:

  • To extend and refine methods for testing and probing moderation in two-instance repeated measures designs.
  • To introduce techniques for handling multiple moderators, including additive and multiplicative moderation.
  • To demonstrate practical application using software tools.

Main Methods:

  • Review and extension of linear regression methods for interaction analysis.
  • Application of pick-a-point and Johnson-Neyman procedures for probing interactions.
  • Development of models for multiple moderators (additive and multiplicative).

Main Results:

  • The article provides extended methods for estimating and probing interactions in repeated measures designs.
  • New approaches for multiple moderator models are presented and demonstrated.
  • Software demonstrations (Mplus, MEMORE for SPSS/SAS) reduce computational complexity.

Conclusions:

  • The developed methods offer comprehensive tools for analyzing moderation in repeated measures.
  • The study facilitates more rigorous investigation of complex moderation hypotheses.
  • Future research directions for advanced moderation analysis are suggested.