Journal
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume 100, Issue 469, Pages 172-183Publisher
AMER STATISTICAL ASSOC
DOI: 10.1198/016214504000000845
Keywords
confidence band; kernel estimation; martingale; model checking and selection; partial likelihood; prediction; survival analysis
Categories
Ask authors/readers for more resources
In the analysis of censored failure time observations, the standard Cox proportional hazards model assumes that the regression coefficients are time invariant. Often, these parameters vary over time, and the temporal covariate effects on the failure time are of great interest. In this article, following previous work of Cai and Sun, we propose a simple estimation procedure for the Cox model with time-varying coefficients based on a kernel-weighted partial likelihood approach. We construct pointwise and simultaneous confidence intervals for the regression parameters over a properly chosen time interval via a simple resampling technique. We derive a prediction method for future patients' survival with any specific set of covariates. Building on the estimates for the time-varying coefficients, we also consider the mixed case and present an estimation procedure for time-independent parameters in the model. Furthermore. we show how to use an integrated function of the estimate for a specific regression coefficient to examine the adequacy of proportional hazards assumption for the corresponding covariate graphically and numerically. All of the proposals are illustrated extensively with a well-known study from the Mayo Clinic.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available