Repeated measures experimental designs, often referred to as "within-subjects" designs, offer researchers opportunities to study research effects while "controlling" for subjects. These designs offer greater statistical power relative to sample size. However, threats to internal validity such as carryover or practice effects need to be taken into consideration. Once data are gathered, researchers have several options for data analysis. If univariate statistical methods are used, omnibus tests can be used, but they must be evaluated for violation of the sphericity assumption, or planned comparisons can be used. Researchers may also use multivariate statistical methods or they may implement both univariate and multivariate approaches while controlling for experiment-wise error. This paper considers both univariate and multivariate approaches to analyzing repeated measures design. Within the univariate discussion, analysis of variance and regression approaches are compared. Also, the assumptions necessary to perform statistical significance tests and how to investigate possible violations of the sphericity assumption are discussed. (Contains six tables and eight references.) (Author/SLD)
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Note:
Paper presented at the Annual Meeting of the Southwest Educational Research Association (Austin, TX, January 23-25, 1997).
Identifiers:
Practice Effects; Repeated Measures Design; Sphericity Tests; Univariate Analysis