Case-cohort analysis with accelerated failure time model

Lan Kong, Jianwen Cai

Research output: Contribution to journalArticle

28 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)135-142
Number of pages8
JournalBiometrics
Volume65
Issue number1
DOIs
StatePublished - Mar 1 2009

Fingerprint

Accelerated Failure Time Model
Cohort Studies
Estimator
Covariates
Case-cohort Design
Rare Diseases
cohort studies
Decelerate
cardiovascular diseases
Statistical methods
Cohort Study
Cardiovascular Diseases
statistical analysis
Relative Efficiency
Semiparametric Model
Statistical method
Asymptotic Properties
Accelerate
Simulation Study
Entire

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

Kong, Lan ; Cai, Jianwen. / Case-cohort analysis with accelerated failure time model. In: Biometrics. 2009 ; Vol. 65, No. 1. pp. 135-142.
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Case-cohort analysis with accelerated failure time model. / Kong, Lan; Cai, Jianwen.

In: Biometrics, Vol. 65, No. 1, 01.03.2009, p. 135-142.

Research output: Contribution to journalArticle

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