Abstract
This paper studies linear nonparametric rank tests for dependent censoring in survival analysis. A method is proposed for testing the assumption of independent censoring, in which a random subset of lost-to-follow-up censored subjects is subsequently followed. Linear nonparametric rank tests and their asymptotic properties are derived by way of the multivariate counting process and multiplicative intensity model proposed by Gill (1980) and Aalen (1978). It is also shown that the proposed linear nonparametric rank tests are equivalent to a class of weighted score statistics for a Cox proportional hazards model. Some simulation results are given for the power of log rank and Wilcoxon-type tests under the propotional hazards alternative and nonpropotional hazards alternative, respectively.
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