Power of models in longitudinal study: Findings from a full-crossed simulation design

Hua Fang, Gordon Brooks, Maria Rizzo, Kimberly Espy, Robert Barcikowski

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Because the power properties of traditional repeated measures and hierarchical multivariate linear models have not been clearly determined in the balanced design for longitudinal studies in the literature, the authors present a power comparison study of traditional repeated measures and hierarchical multivariate linear models under 3 variance-covariance structures. The results from a full-crossed simulation design suggest that traditional repeated measures have significantly higher power than do hierarchical multivariate linear models for main effects, but they have significantly lower power for interaction effects in most situations. Significant power differences are also exhibited when power is compared across different covariance structures.

Original languageEnglish (US)
Pages (from-to)215-254
Number of pages40
JournalJournal of Experimental Education
Volume77
Issue number3
DOIs
StatePublished - Apr 1 2009

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Keywords

  • Covariance structure
  • Hierarchical multivariate linear models
  • Longitudinal study
  • Power analysis
  • Traditional repeated measures

ASJC Scopus subject areas

  • Education
  • Developmental and Educational Psychology

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