Literature DB >> 18537948

Case-cohort analysis with accelerated failure time model.

Lan Kong1, Jianwen Cai.   

Abstract

In a case-cohort design, covariates are assembled only for a subcohort that is randomly selected from the entire cohort and any additional cases outside the subcohort. This design is appealing for large cohort studies of rare disease, especially when the exposures of interest are expensive to ascertain for all the subjects. We propose statistical methods for analyzing the case-cohort data with a semiparametric accelerated failure time model that interprets the covariates effects as to accelerate or decelerate the time to failure. Asymptotic properties of the proposed estimators are developed. The finite sample properties of case-cohort estimator and its relative efficiency to full cohort estimator are assessed via simulation studies. A real example from a study of cardiovascular disease is provided to illustrate the estimating procedure.

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Year:  2008        PMID: 18537948      PMCID: PMC2990888          DOI: 10.1111/j.1541-0420.2008.01055.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  5 in total

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2.  Likelihood analysis of multi-state models for disease incidence and mortality.

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  10 in total

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