title: More efficient estimators for case-cohort studies.
abstract: The case-cohort study design, used to reduce costs in large cohort studies, is a random sample of the entire cohort, named the subcohort, augmented with subjects having the disease of interest but not in the subcohort sample. When several diseases are of interest, several case-cohort studies may be conducted using the same subcohort, with each disease analyzed separately, ignoring the additional exposure measurements collected on subjects with the other diseases. This is not an efficient use of the data, and in this paper, we propose more efficient estimators. We consider both joint and separate analyses for the multiple diseases. We propose an estimating equation approach with a new weight function, and we establish the consistency and asymptotic normality of the resulting estimator. Simulation studies show that the proposed methods using all available information gain efficiency. We apply our proposed method to the data from the Busselton Health Study.
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, U.S.A.
authors.forename: S
authors.initials: S
authors.lastname: Kim
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, U.S.A.
authors.forename: J
authors.initials: J
authors.lastname: Cai
authors.affiliation: Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695, U.S.A.
authors.forename: W
authors.initials: W
authors.lastname: Lu
keywords: Case-cohort study; Multiple disease outcomes; Multivariate failure time; Proportional hazards; Survival analysis