Improving efficiency of parameter estimation in case-cohort studies with multivariate failure time data.

TitleImproving efficiency of parameter estimation in case-cohort studies with multivariate failure time data.
Publication TypeJournal Article
Year of Publication2017
AuthorsYan Y, Zhou H, Cai J
JournalBiometrics
Volume73
Issue3
Pagination1042-1052
Date Published2017 09
ISSN1541-0420
KeywordsCohort Studies, Computer Simulation, Data Interpretation, Statistical
Abstract

The case-cohort study design is an effective way to reduce cost of assembling and measuring expensive covariates in large cohort studies. Recently, several weighted estimators were proposed for the case-cohort design when multiple diseases are of interest. However, these existing weighted estimators do not make effective use of the covariate information available in the whole cohort. Furthermore, the auxiliary information for the expensive covariates, which may be available in the studies, cannot be incorporated directly. In this article, we propose a class of updated-estimators. We show that, by making effective use of the whole cohort information, the proposed updated-estimators are guaranteed to be more efficient than the existing weighted estimators asymptotically. Furthermore, they are flexible to incorporate the auxiliary information whenever available. The advantages of the proposed updated-estimators are demonstrated in simulation studies and a real data analysis.

DOI10.1111/biom.12657
Alternate JournalBiometrics
Original PublicationImproving efficiency of parameter estimation in case-cohort studies with multivariate failure time data.
PubMed ID28112795
PubMed Central IDPMC5522786
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 ES021900 / ES / NIEHS NIH HHS / United States