Cox Regression Model with Time-Varying Coefficients in Nested Case-Control Studies

• Activity Number: 231
• Type: Topic Contributed
• Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Section on Nonparametric Statistics
• Author(s): Mengling Liu*+ and Wenbin Lu and Anne Zeleniuch-Jacquotte and Roy E. Shore
• Companies: New York University School of Medicine and North Carolina State University and New York University School of Medicine and Radiation Effects Research Foundation
• Keywords: Kernel estimation ; Martingale ; Nested case-control study ; Proportional hazards model ; Risk-set sampling ; Time-varying coefficient

Abstract

The nested case-control (NCC) design is a cost-effective sampling method to study the relationship of disease with risk factors in large prospective epidemiologic studies. NCC data are commonly analyzed using Thomas' partial likelihood approach under Cox's proportional hazards model with constant covariate effects. Here, we are interested in studying the potential time-varying effects of risk factors on disease risk in NCC studies and propose an estimation approach based on kernel-weighted Thomas' partial likelihood. We establish the asymptotic properties of the proposed estimator, propose a numerical approach to construct simultaneous confidence bands of time-varying coefficients, and develop a hypothesis testing procedure to detect time-varying coefficient using the integrated function of the time-varying estimate.