Rank-based regression for analysis of repeated measures

We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then...

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Bibliographic Details
Published inBiometrika Vol. 93; no. 2; pp. 459 - 464
Main Authors Zhu, Min, Wang, You-Gan
Format Journal Article
LanguageEnglish
Published Oxford University Press for Biometrika Trust 01.06.2006
SeriesBiometrika
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Summary:We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then introduced to generate bootstrap replicates of the estimating functions and the parameter estimates. This provides a convenient way for combining the corresponding two types of estimating function for more efficient estimation. Copyright 2006, Oxford University Press.
ISSN:0006-3444
1464-3510
DOI:10.1093/biomet/93.2.459