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The trick is to convert the multiple Bout measurements into a single value for each subject, then analyze those values. Y pre mid post Trial Subject: JC Patterns of Responses: by Within-Subject Modeling Derive the change in meanand the change in slopebetween pre and post(or any other Trials) for each subject. For the changes in the mean, do an unpaired t test between the exptal and control groups. Ditto for the changes in the slope. Simple, robust, highly recommended! In the example, derive the Bout mean and slope (or any other parameters) within each trial for each subject. Analyzing for Mechanisms How much of the change was due to a change in whatever? It does not apply to nominal dependent variables or variables representing counts or frequencies. This presentation applies to continuous or ordinal numeric dependent variables, including data from most Likert scales. Analysis of Repeated MeasuresWill G Hopkins, Auckland University of Technology, Auckland, NZ A tutorial lecture presented at the 2003 annual meetingof the American College of Sports Medicine Make sure you view this presentation as a full slide show, to get the benefit of the build-up of information on each slide. OVERVIEW Basics What change has occurred in response to a treatment/intervention? Analysis by ANOVA, within-subject modeling, mixed modeling. Fixed and random effects; individual responses and asphericity. Accounting for Individual Responses What is the effect of subject characteristics on the change? Analyzing for Patterns of Responses What is the treatments effect on trends in repeated sets of trials? Analyzing for Mechanisms How much of the change was due to a change in whatever? Basics What change has occurred in response to a treatment or intervention? A repeated measure is a variable measured two or more times, usually before, during and/or after an intervention or treatment. Analysis by ANOVA, t statistics and within-subject modeling, and mixed modeling. Data are means a
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