Weighted rank regression for clustered data analysis

Wang, You-Gan and Zhao, Yudong (2008) Weighted rank regression for clustered data analysis. Biometrics, 64 1: 39-45. doi:10.1111/j.1541-0420.2007.00842.x

Author Wang, You-Gan
Zhao, Yudong
Title Weighted rank regression for clustered data analysis
Journal name Biometrics   Check publisher's open access policy
ISSN 0006-341X
Publication date 2008-03
Sub-type Article (original research)
DOI 10.1111/j.1541-0420.2007.00842.x
Volume 64
Issue 1
Start page 39
End page 45
Total pages 7
Place of publication Oxford, United Kingdom
Publisher Wiley-Blackwell Publishing
Language eng
Abstract We consider ranked-based regression models for clustered data analysis. A weighted Wilcoxon rank method is proposed to take account of within-cluster correlations and varying cluster sizes. The asymptotic normality of the resulting estimators is established. A method to estimate covariance of the estimators is also given, which can bypass estimation of the density function. Simulation studies are carried out to compare different estimators for a number of scenarios on the correlation structure, presence/absence of outliers and different correlation values. The proposed methods appear to perform well, in particular, the one incorporating the correlation in the weighting achieves the highest efficiency and robustness against misspecification of correlation structure and outliers. A real example is provided for illustration.
Keyword Clustered data
Covariance estimation
Dependent data
Estimating functions
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Mathematics and Physics
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 9 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 17 Nov 2010, 14:11:47 EST