Hierarchical linear model: Thinking outside the traditional repeated-measures analysis-of-variance box

Monica Lininger, Jessaca Spybrook, Christopher C. Cheatham

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Longitudinal designs are common in the field of athletic training. For example, in the Journal of Athletic Training from 2005 through 2010, authors of 52 of the 218 original research articles used longitudinal designs. In 50 of the 52 studies, a repeatedmeasures analysis of variance was used to analyze the data. A possible alternative to this approach is the hierarchical linear model, which has been readily accepted in other medical fields. In this short report, we demonstrate the use of the hierarchical linear model for analyzing data from a longitudinal study in athletic training. We discuss the relevant hypotheses, model assumptions, analysis procedures, and output from the HLM 7.0 software. We also examine the advantages and disadvantages of using the hierarchical linear model with repeated measures and repeated-measures analysis of variance for longitudinal data.

Original languageEnglish (US)
Pages (from-to)438-441
Number of pages4
JournalJournal of athletic training
Volume50
Issue number4
DOIs
StatePublished - Apr 1 2015

Keywords

  • Longitudinal designs in athletic training
  • Statistical analysis

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine
  • Physical Therapy, Sports Therapy and Rehabilitation

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