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Doctoral Dissertation Announcement
Candidate: Monica R. Lininger
Doctor of Philosophy
Department: Educational Leadership, Research and Technology
Title: Examining the Research Designs and Analytical Techniques in Athletic Training from 2005 – 2010
Dr. Jessaca Spybrook, Chair
Dr. Brooks Applegate
Dr. Chris Cheatham
Date: Thursday, February 23, 2012 9:00 a.m. to 11:00 a.m.
3514 Sangren Hall
In May 2010, an editorial board member for the Journal of Athletic Training (JAT), the top rated journal in this field, published an editorial calling for a change in the terminology of the design section of future manuscript submissions. The intent was to align the design section of articles in the JAT with other journals in medicine. The editorial identified 13 design categories, and while this is a critical first step in indentifying the research design, it would be argued that further detail should be included in the design section. This is critical since the appropriate analyses hinge on the research design.
In athletic training, longitudinal designs are very common. The study reviewed the published articles in the JAT from 2005 – 2010 and found the most common method to analyze data from longitudinal designs is a repeated measures analysis of variance (RM ANOVA). Numerous assumptions must be met for the results from a RM ANOVA to be valid. It is common that these assumptions are not met in longitudinal designs. The purpose of this dissertation is to present an alternative statistical method for data from longitudinal designs, compared to the traditional RM ANOVA. The research proposes using a hierarchical linear model (HLM) which has been more commonly used, with success, in other medical fields.
Through a purposeful random sampling, 18 corresponding authors with articles in the JAT from 2005-2010 that had a longitudinal design and used a RM ANOVA were contacted through e-mail. Nine authors were willing to provide the de-identified data presented in the journal article.
This study replicated the two-way RM ANOVA described in the published article and compared the findings to the published results. Only two articles mentioned assumption testing. Yet reanalysis revealed that the assumption of sphericity was violated in all datasets. The research then used an HLM to reexamine the same data. The HLM analysis focuses on modeling individual growth trajectories and answers different questions than the RM ANOVA. However, practical implications can be drawn from either analysis. The practical implications were similar using either HLM or RM ANOVA in 4 cases and differed in 4 cases.