Zhang, Ying Nonparametric \(k\)-sample tests with panel count data. (English) Zbl 1436.62158 Biometrika 93, No. 4, 777-790 (2006). Summary: 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 [J. A. Wellner and Y. Zhang, Ann. Stat. 28, No. 3, 779–814 (2000; Zbl 1105.62372)] 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 good power to detect differences among the mean functions. The method is illustrated with a real-life example. Cited in 29 Documents MSC: 62G10 Nonparametric hypothesis testing 62G20 Asymptotic properties of nonparametric inference 62E20 Asymptotic distribution theory in statistics Keywords:counting process; empirical process; interval censored data; isotonic regression; Monte Carlo Citations:Zbl 1105.62372 PDFBibTeX XMLCite \textit{Y. Zhang}, Biometrika 93, No. 4, 777--790 (2006; Zbl 1436.62158) Full Text: DOI