A practical divergence measure for survival distributions that can be estimated from Kaplan-Meier curves

(2015) A practical divergence measure for survival distributions that can be estimated from Kaplan-Meier curves. Statistics in Medicine. ISSN 0277-6715 (Submitted)

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Abstract

This paper introduces a new simple divergence measure between two survival distributions. For two groups of patients, the divergence measure between their associated survival distributions is based on the integral of the absolute difference in probabilities that a patient from one group dies at time t and a patient from the other group survives beyond time t and vice versa. In the case of non-crossing hazard functions, the divergence measure reduces to the absolute difference of the expected values of one survival function with respect to the distribution of the other. The measure can be used in a dynamic way where the divergence between two survival distributions from time zero up to time t is calculated enabling real-time monitoring of treatment differences. The divergence can be found for theoretical survival distributions or can be estimated non-parametrically from survival data using Kaplan-Meier estimates of the survivor functions. The estimator of the divergence is shown to be asymptotically unbiased and normally distributed. For the case of proportional hazards, the constituent parts of the divergence measure can be used to assess the proportional hazards assumption. The use of the divergence measure is illustrated on the survival of pancreatic cancer patients.

Item Type:	Article
Additional Information:	Provisionally accepted for publication
Depositing User:	Symplectic Admin
Date Deposited:	31 Mar 2016 10:03
Last Modified:	31 Mar 2016 10:03
URI:	http://livrepository.liverpool.ac.uk/id/eprint/2022417

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