A simple nonparametric two-sample test for the distribution function of event time with interval censored data

Ying Zhang, Wei Liu, Hulin Wu

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

For the setting of interval censored data in which the event time is not exactly observed but known to be inside a random interval, a simple nonparametric two-sample test, based on empirical estimates of smooth functionals of the distribution function of event time, is developed to compare the distribution functions of event time for two populations. Monte Carlo simulation studies on Weibull distributions show that this test performs quite well. A real data set from an AIDS clinical trial is used to illustrate the test.

Original languageEnglish (US)
Pages (from-to)643-652
Number of pages10
JournalJournal of Nonparametric Statistics
Volume15
Issue number6
DOIs
StatePublished - Dec 1 2003
Externally publishedYes

Keywords

  • Asymptotic normality
  • Distribution function of event time
  • Empirical estimate
  • Interval censoring
  • Monte Carlo Simulation
  • Panel Count Data
  • Pseudolikelihood estimate

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint Dive into the research topics of 'A simple nonparametric two-sample test for the distribution function of event time with interval censored data'. Together they form a unique fingerprint.

  • Cite this