Improving Efficiency of Parameter Estimation in Case-Cohort Studies

• Activity Number: 495
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: SSC
• Author(s): Ying Yan* and Haibo Zhou and Jianwen Cai
• Companies: and The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
• Keywords: auxiliary information ; multivariate failure time ; proportional hazards model ; updated estimators ; weighted estimators

Abstract

The case-cohort design is a widely used tool to reduce costs of covariate measurements in large cohort studies. Recently, several weighted estimators are proposed for the case-cohort design when multiple diseases are of interest. However, these existing weighted estimators do not effectively make use of the information available in the whole cohort. Furthermore, the auxiliary information, when it is available, can not be incorporated by the existing weighted estimators. In this talk, we propose a class of updated estimators. We show that the proposed updated estimators are guaranteed to be more efficient than the existing weighted estimators theoretically. Furthermore, they are flexible to incorporate auxiliary information whenever available. The advantages of the proposed updated estimators are demonstrated in simulation studies and real data analysis.