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Focusing on the analysis of repeated-measures data, this thesis explores both univariate and multivariate methodologies. It addresses the common issue of correlated measurements over time, which challenges the independence assumption of traditional analysis of variance. By presenting various models, the work emphasizes the strengths and weaknesses of each approach, providing valuable insights for researchers dealing with similar statistical challenges.
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Univariate and Multivariate Methods for the Analysis of Repeated Measures Data, Tony Wragg
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- 2011
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