The analysis of repeated measures design: A review

Department of Psychology, University of Manitoba, 190 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2.
British Journal of Mathematical and Statistical Psychology (Impact Factor: 2.17). 06/2001; 54(Pt 1):1-20. DOI: 10.1348/000711001159357
Source: PubMed


Repeated measures ANOVA can refer to many different types of analysis. Specifically, this vague term can refer to conventional tests of significance, one of three univariate solutions with adjusted degrees of freedom, two different types of multivariate statistic, or approaches that combine univariate and multivariate tests. Accordingly, it is argued that, by only reporting probability values and referring to statistical analyses as repeated measures ANOVA, authors convey neither the type of analysis that was used nor the validity of the reported probability value, since each of these approaches has its own strengths and weaknesses. The various approaches are presented with a discussion of their strengths and weaknesses, and recommendations are made regarding the 'best' choice of analysis. Additional topics discussed include analyses for missing data and tests of linear contrasts.

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    • "In cases of the violation of the assumption of sphericity, Greenhouse Geisser corrected p-values for the F-statistics are reported. Unequal sample sizes and heterogeneous variances between groups may lead to progressive decisions in favour of the H1 [82]. Therefore, we subsequently inspected significant repeated measures ANOVA effects by means of the Welch test (Table 1), when heterogeneous variances are assumed. "
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