JEL Ratio Test for Independence of Time to Failure and Cause of Failure in Competing Risks Data

Abstract

In the present article, we propose a Jackknife empirical likelihood (JEL) ratio test for testing the independence of time to failure and cause of failure in competing risks data. We use the U-statistics theory to derive the JEL ratio test. The asymptotic distribution of the test statistic is shown to be the standard chi-square distribution. A Monte Carlo simulation study is carried out to assess the finite sample behavior of the proposed test. The performance of the proposed JEL test is compared with the test given by Dewan et al. (2004). Finally, we illustrate our test procedure using two real data sets.

Keywords

• chi square distribution
• competing risks
• conditional probability
• jackknife empirical likelihood
• u-statistics