Trend analysis for repeated measures designs

This paper outlines a method of analysis that is well-suited to repeated measures designs. This method uses polynomial functions of time to characterize an outcome variable measured at several distinct time points on the same subjects. Profiles for different treatment groups may be compared using th...

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Bibliographic Details
Published in:Medicine and science in sports and exercise 1990-12, Vol.22 (6), p.871
Main Authors: Holbert, D, Chenier, T C, O'Brien, K F
Format: Article
Language:English
Subjects:
Absenteeism
Analysis of Variance
Exercise - physiology
Humans
Male
Physiology - methods
Plants, Toxic
Regression Analysis
Research Design
Smoking
Software
Sports Medicine
Time
Tobacco, Smokeless
Weights and Measures
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Summary:This paper outlines a method of analysis that is well-suited to repeated measures designs. This method uses polynomial functions of time to characterize an outcome variable measured at several distinct time points on the same subjects. Profiles for different treatment groups may be compared using the appropriate interaction terms in an analysis of variance table. The method is illustrated with data from two recent studies.
ISSN:0195-9131
DOI:10.1249/00005768-199012000-00022