Use of log−log survival function in modeling time-covariate interactions in Cox regression |
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Authors: | Mizanur R. Khondoker M. Ataharul Islam |
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Affiliation: | 1. Division of Pathway Medicine (DPM), The University of Edinburgh Medical School, The Chancellor''s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK;2. Department of Statistics, University of Dhaka, Dhaka 1000, Bangladesh |
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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. |
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Keywords: | Hazard functions Proportional hazards Partial likelihood Log&minus log survival function Censoring Score test |
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