IPCW approach for testing independence

Abstract

Here we present a novel inverse probability of censoring weighted (IPCW) adaptation of the Kochar–Gupta (KG) test of independence, in the case of bivariate randomly censored data. Three different censoring schemes are considered: one of the target variables is censored, both targeted variables are censored with the same censoring variable, and both target variables are censored with different censoring variables. The limiting properties of test statistics are explored. In order to compare the tests with a few well-known competitors in terms of powers, several resampling procedures have been utilised to approximate the null distribution. Special attention is dedicated to the comparison with a classical adaptation of the KG test related to the IPCW adaptation of U-statistics.