Nonparametric K-Sample Tests with Panel Count Data
نویسنده
چکیده
In this manuscript, we study the nonparametric k-sample test problem with panel count data. The asymptotic normality of a smooth functional of the nonparametric maximum pseudo-likelihood estimator (Wellner and Zhang, 2000) is established under some mild conditions. We construct a class of easy-to-implement nonparametric tests for comparing mean functions of k populations based on this asymptotic normality. We conduct various simulations to validate and compare the tests. The simulations show that the tests perform quite well and generally have a good power to detect difference of the mean functions. The method is illustrated with two real data examples. Some key words: Counting Process; Empirical Process; Interval censored data; Monte-Carlo; Isotonic Regression.
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