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Activity Number: 18
Type: Topic Contributed
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: International Chinese Statistical Association
Abstract #317059
Title: Partially Time-Varying Coefficient Proportional Hazards Models with Time-Dependent Covariates Measured with Error
Author(s): Xiao Song* and Lily Wang
Companies: University of Georgia and Iowa State University
Keywords: Corrected score ; Conditional score ; Joint modeling ; Measurement error ; Polynomial spline
Abstract:

Joint models are often used for survival data with time-dependent covariates. Motivated by recent works studying the AIDS Clinical Trial Group (ACTG) 175 data, we propose a partially time-varying coefficient proportional hazards model for modeling the relationship between the hazard of failure and time-dependent and time-independent covariates. The time-varying coefficients are approximated by polynomial splines, and the corrected score and conditional score approaches are adopted to estimate the regression coefficients. The convergence rate of the estimators is derived, and the asymptotic normality is established for the constant coefficients. The finite-sample performance of the proposed method is assessed by Monte Carlo simulation studies. The proposed model is applied to ACTG 175 data to assess the temporal dynamics of the effect of treatment and CD4 count on time to AIDS or death.


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