Rank-based regression for analysis of repeated measures

被引：22

作者：

Wang, You-Gan ^{[1
]}

Zhu, Min ^{[1
]}

机构：

[1] CSIRO Math & Informat Sci, Leeuwin Ctr, Floreat, WA 6014, Australia

来源：

BIOMETRIKA | 2006年 / 93卷 / 02期

关键词：

bootstrap; covariance model; dependent data; estimating function; longitudinal data; rank estimation; repeated measures; Wilcoxon method;

D O I：

10.1093/biomet/93.2.459

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页码：459 / 464

页数：6

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