Cox regression model with time-varying coefficients in nested case-control studies.
The nested case-control (NCC) design is a cost-effective sampling method to study the relationship between a disease and its risk factors in 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 covariates in NCC studies and propose an estimation approach based on a kernel-weighted Thomas' partial likelihood. We establish asymptotic properties of the proposed estimator, propose a numerical approach to construct simultaneous confidence bands for time-varying coefficients, and develop a hypothesis testing procedure to detect time-varying coefficients. The proposed inference procedure is evaluated in simulations and applied to an NCC study of breast cancer in the New York University Women's Health Study.
Liu
Mengling
M
Department of Environmental Medicine, New York University School of Medicine, New York, NY 10016, USA. mengling.liu@nyu.edu
Lu
Wenbin
W
Shore
Roy E
RE
Zeleniuch-Jacquotte
Anne
A
D000367:Age Factors; D000368:Aged; D000465:Algorithms; D056808:Biostatistics / Q000379:methods*; D001943:Breast Neoplasms / Q000453:epidemiology / Q000235:genetics; D016022:Case-Control Studies; D003198:Computer Simulation; D004268:DNA-Binding Proteins / Q000235:genetics; D005260:Female; D006801:Humans; D015994:Incidence; D016013:Likelihood Functions; D008875:Middle Aged; D016016:Proportional Hazards Models; D012306:Risk; D018401:Sample Size; D012907:Smoking / Q000235:genetics; D013997:Time Factors
D004268:DNA-Binding Proteins; C086984:XPC protein, human