Abstract
It is typical in survival analysis that the quantities of interest are only partially observable. One encounters data being censored, truncated or interval censored. When testing a control versus a treatment group in such a situation one gets an additional complication, namely infinite-dimensional nuisance parameters representing the censoring and truncation distributions. In this paper, we review a method for constructing in some sense asymptotically optimal rank tests when data are only partially observed.
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