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Statistical power for repeated measures anova

University of British Columbia

Determining power a prior for univariate repeated measures (RM) ANOVA designs is a difficult and often excluded practice in the planning of experimental research. Complicated procedures and lack of accessibility to computer power programs are among some of the problems which have discouraged researchers from perforrning power analysis on these designs. Another more serious issue has been the lack of methods available for estimating power of designs with two or more R M factors. Due to uncertainties on how to compute an appropriate error term when more than one variance-covariance matrix exists, analytical methods for approximating power are currently restricted to R M designs with only one withinsubjects variable. The purpose of this study therefore, was to facilitate the process of power detennination by providing a series of power tables for ANOVA designs with one and two within-subject variables. A secondary objective was to investigate less well known power trends among ANOVA designs having heterogeneous (nonspherical) correlation matrices or two R M factors. Power was generated using analytical and Monte Carlo simulation methods for varying experimental conditions of sample size (5, 10 , 15, 20, 25 & 30), effect size (small, medium & large), alpha (.01, .05 & .10), correlation (.4 & .8), variance-covariance matrix patterns (constant, e=1.00 and trend, e

Thesis/Dissertation

application/pdf

2009-02-17

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http://hdl.handle.net/2429/4644

Human Kinetics

University of British Columbia

UBCV

DSpace