Case influence diagnostics in the kaplan-meier estimator and the log-rank test

One or few observations can be highly influential on the Kaplan-Meier estimator, and consequently on the log-rank test statistic in comparing two survival functions. In this paper we derive case influence diagnostics for the Kaplan-Meier estimator and the log-rank test. We note that diagnostics in this context is quite different from the regression context where observations are usually assumed to be independent. Simulation studies are done to present some guidelines to determine influential observations deserving special attention. Illustrative examples are also given.