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Linear Nonparametric Tests for Comparison of Counting Processes, with Applications to Censored Survival Data

机译：用于比较计数过程的线性非参数检验，以及对截尾生存数据的应用

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Linear nonparametric one- and k-sample tests for counting processes are surveyed. The necessary probabilistic background is outlined and a master theorem proved, which may be specialized to most known asymptotic results for linear rank tests for censored data as well as to asymptotic results for one- and k-sample tests in more general situations, an important feature being that very general censoring patterns are allowed. A survey is given of existing tests and their relation to the general theory, and examples of applications to Markov processes are provided. The relation of the approach to classical nonparametric hypothesis testing theory based on permutation distributions is also discussed.

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