Rank regression for accelerated failure time model with clustered and censored data
Wang, You-Gan & Fu, Liya (2011) Rank regression for accelerated failure time model with clustered and censored data. Computational Statistics & Data Analysis, 55(7), pp. 2334-2343.
For clustered survival data, the traditional Gehan-type estimator is asymptotically equivalent to using only the between-cluster ranks, and the within-cluster ranks are ignored. The contribution of this paper is two fold:
(i) incorporating within-cluster ranks in censored data analysis, and;
(ii) applying the induced smoothing of Brown and Wang (2005, Biometrika) for computational convenience.
Asymptotic properties of the resulting estimating functions are given. We also carry out numerical studies to assess the performance of the proposed approach and conclude that the proposed approach can lead to much improved estimators when strong clustering effects exist. A dataset from a litter-matched tumorigenesis experiment is used for illustration.
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|Item Type:||Journal Article|
|Keywords:||Clustered data, Covariance matrix, Gehan-type weight function, Induced, smoothing, Rank estimation, Survival data, linear-models, large-sample, distributions|
|Divisions:||Current > QUT Faculties and Divisions > Science & Engineering Faculty|
|Deposited On:||17 Nov 2015 05:13|
|Last Modified:||03 Dec 2015 05:13|
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