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The analysis of repeated measures designs: A review
Author(s) -
Keselman H. J.,
Algina James,
Kowalchuk Rhonda K.
Publication year - 2001
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1348/000711001159357
Subject(s) - univariate , strengths and weaknesses , statistic , repeated measures design , statistics , multivariate statistics , multivariate analysis , type i and type ii errors , statistical analysis , multivariate analysis of variance , statistical hypothesis testing , analysis of variance , term (time) , econometrics , mathematics , computer science , psychology , social psychology , physics , quantum mechanics
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.