Nonparametric k-sample tests with panel count data

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


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 & 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 good power to detect differences among the mean functions. The method is illustrated with a real-life example.

Original languageEnglish (US)
Pages (from-to)777-790
Number of pages14
Issue number4
StatePublished - Dec 2006
Externally publishedYes


  • Counting process
  • Empirical process
  • Interval censored data
  • Isotonic regression
  • Monte Carlo

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


Dive into the research topics of 'Nonparametric k-sample tests with panel count data'. Together they form a unique fingerprint.

Cite this