Title

A Simple Nonparametric Two-Sample Test For The Distribution Function Of Event Time With Interval Censored Data

Keywords

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

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.

Publication Date

12-1-2003

Publication Title

Journal of Nonparametric Statistics

Volume

15

Issue

6

Number of Pages

643-652

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1080/10485250310001624530

Socpus ID

0347569232 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0347569232

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