4.5 Article

Hypothesis Testing for an Extended Cox Model with Time-Varying Coefficients

Journal

BIOMETRICS
Volume 70, Issue 3, Pages 619-628

Publisher

WILEY-BLACKWELL
DOI: 10.1111/biom.12185

Keywords

Censoring; Clinical trials; HIV; AIDS; Log-rank test; Score test

Funding

  1. NIH grants [R01AI089341, P01CA53996]
  2. NIH [R21ES022332, R01AG014358, R01HG006124]

Ask authors/readers for more resources

The log-rank test has been widely used to test treatment effects under the Cox model for censored time-to-event outcomes, though it may lose power substantially when the model's proportional hazards assumption does not hold. In this article, we consider an extended Cox model that uses B-splines or smoothing splines to model a time-varying treatment effect and propose score test statistics for the treatment effect. Our proposed new tests combine statistical evidence from both the magnitude and the shape of the time-varying hazard ratio function, and thus are omnibus and powerful against various types of alternatives. In addition, the new testing framework is applicable to any choice of spline basis functions, including B-splines, and smoothing splines. Simulation studies confirm that the proposed tests performed well in finite samples and were frequently more powerful than conventional tests alone in many settings. The new methods were applied to the HIVNET 012 Study, a randomized clinical trial to assess the efficacy of single-dose Nevirapine against mother-to-child HIV transmission conducted by the HIV Prevention Trial Network.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available