Asymptotic results for fitting marginal hazard models from stratified case-cohort studies with multiple disease outcomes

Sangwook Kang, Jianwen Cai

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In stratified case-cohort designs, samplings of case-cohort samples are conducted via a stratified random sampling based on covariate information available on the entire cohort members. In this paper, we extended the work of Kang and Cai (2009) to a generalized stratified case-cohort study design for failure time data with multiple disease outcomes. Under this study design, we developed weighted estimating procedures for model parameters in marginal multiplicative intensity models and for the cumulative baseline hazard function. The asymptotic properties of the estimators are studied using martingales, modern empirical process theory, and results for finite population sampling.

Original languageEnglish
Pages (from-to)371-385
Number of pages15
JournalJournal of the Korean Statistical Society
Volume39
Issue number3
DOIs
Publication statusPublished - 2010 Sep 1

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Case-cohort Design
Marginal Model
Hazard Models
Cohort Study
Finite Population Sampling
Stratified Random Sampling
Failure Time Data
Hazard Function
Empirical Process
Martingale
Asymptotic Properties
Covariates
Baseline
Multiplicative
Entire
Estimator
Model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Cite this

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