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Marginal Analysis of Correlated Failure Time Data with Informative Cluster Sizes
Author(s) -
Cong Xiuyu J.,
Yin Guosheng,
Shen Yu
Publication year - 2007
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2006.00730.x
Subject(s) - estimator , resampling , statistics , consistency (knowledge bases) , mathematics , proportional hazards model , cluster (spacecraft) , asymptotic distribution , regression , econometrics , sample (material) , estimating equations , computer science , geometry , programming language , chemistry , chromatography
Summary We consider modeling correlated survival data when cluster sizes may be informative to the outcome of interest based on a within‐cluster resampling (WCR) approach and a weighted score function (WSF) method. We derive the large sample properties for the WCR estimators under the Cox proportional hazards model. We establish consistency and asymptotic normality of the regression coefficient estimators, and the weak convergence property of the estimated baseline cumulative hazard function. The WSF method is to incorporate the inverse of cluster sizes as weights in the score function. We conduct simulation studies to assess and compare the finite‐sample behaviors of the estimators and apply the proposed methods to a dental study as an illustration.