FCCC LOGO Faculty Publications
Devarajan K , Ebrahimi N
Testing for Covariate Effect in the Cox Proportional Hazards Regression Model
Commun Stat Theory Methods. 2009 Jan 1;38(14) :2333-2347
PMID: 20054448    PMCID: PMC2802211   
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Abstract
This paper presents methods for testing covariate effect in the Cox proportional hazards Model based on Kullback-Leibler divergence and Renyi's information measure. Renyi's measure is referred to as the information divergence of order gamma (gamma not equal 1) between two distributions. In the limiting case gamma --> 1, Renyi's measure becomes Kullback-Leibler divergence. In our case, the distributions correspond to the baseline and one possibly due to a covariate effect. Our proposed statistics are simple transformations of the parameter vector in the Cox proportional hazards model, and are compared with the Wald, likelihood ratio and Score tests that are widely used in practice. Finally, the methods are illustrated using two real-life data sets.
Notes
P30 CA006927-45S2/NCI NIH HHS/United States Communications in statistics: theory and methods Commun Stat Theory Methods. 2009 Jan 1;38(14):2333-2347.