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Rank repeated measures analysis of covariance

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  • Chunpeng Fan
  • Donghui Zhang

Abstract

When analyzing a response variable at the presence of both factors and covariates, with potentially correlated responses and violated assumptions of the normal residual or the linear relationship between the response and the covariates, rank-based tests can be an option for inferential procedures instead of the parametric repeated measures analysis of covariance (ANCOVA) models. This article derives a rank-based method for multi-way ANCOVA models with correlated responses. The generalized estimating equations (GEE) technique is employed to construct the proposed rank tests. Asymptotic properties of the proposed tests are derived. Simulation studies confirmed the performance of the proposed tests.

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  • Chunpeng Fan & Donghui Zhang, 2017. "Rank repeated measures analysis of covariance," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(3), pages 1158-1183, February.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:3:p:1158-1183
    DOI: 10.1080/03610926.2015.1014106
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    Cited by:

    1. Zimmermann, Georg & Pauly, Markus & Bathke, Arne C., 2020. "Multivariate analysis of covariance with potentially singular covariance matrices and non-normal responses," Journal of Multivariate Analysis, Elsevier, vol. 177(C).

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