Use of log−log survival function in modeling time-covariate interactions in Cox regression

Khondoker, Mizanur R. and Ataharul Islam, M. (2009) Use of log−log survival function in modeling time-covariate interactions in Cox regression. Journal of Statistical Planning and Inference, 139 (6). pp. 1968-1973. ISSN 0378-3758

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Abstract

Plotting of log−log survival functions against time for different categories or combinations of categories of covariates is perhaps the easiest and most commonly used graphical tool for checking proportional hazards (PH) assumption. One problem in the utilization of the technique is that the covariates need to be categorical or made categorical through appropriate grouping of the continuous covariates. Subjectivity in the decision making on the basis of eye-judgment of the plots and frequent inconclusiveness arising in situations where the number of categories and/or covariates gets larger are among other limitations of this technique. This paper proposes a non-graphical (numerical) test of the PH assumption that makes use of log−log survival function. The test enables checking proportionality for categorical as well as continuous covariates and overcomes the other limitations of the graphical method. Observed power and size of the test are compared to some other tests of its kind through simulation experiments. Simulations demonstrate that the proposed test is more powerful than some of the most sensitive tests in the literature in a wide range of survival situations. An example of the test is given using the widely used gastric cancer data.

Item Type: Article
Uncontrolled Keywords: hazard functions,proportional hazards,partial likelihood,log−log survival function,censoring,score test
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
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Depositing User: Pure Connector
Date Deposited: 24 Sep 2016 00:41
Last Modified: 26 Jul 2020 23:40
URI: https://ueaeprints.uea.ac.uk/id/eprint/60178
DOI: 10.1016/j.jspi.2008.08.026

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