作者: Per Kragh Andersen , Ørnulf Borgan , Richard Gill , Niels Keiding , Ornulf Borgan
DOI: 10.2307/1402489
关键词: Econometrics 、 Nonparametric statistics 、 Survival data 、 Applied mathematics 、 Nonparametric hypothesis testing 、 Probabilistic logic 、 Computer science 、 Master theorem 、 Markov process 、 General theory 、 Censoring (statistics)
摘要: This paper surveys linear nonparametric one-and k-sample tests for counting processes. 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 we mention examples of …