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

A simple nonparametric two-sample test for the distribution function of event time with interval censored data
A simple nonparametric two-sample test for the distribution function of event time with interval censored data
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.
asymptotic normality, distribution function of event time, empirical estimate, interval censoring, Monte Carlo simulation, panel count data, pseudolikelihood estimate
1048-5252
643-652
Zhang, Ying
a1a5b530-992a-41b3-94d8-043590122036
Liu, Wei
b64150aa-d935-4209-804d-24c1b97e024a
Wu, Hulin
6ec35e5a-25ea-4eae-8584-56b01b2c1c75
Zhang, Ying
a1a5b530-992a-41b3-94d8-043590122036
Liu, Wei
b64150aa-d935-4209-804d-24c1b97e024a
Wu, Hulin
6ec35e5a-25ea-4eae-8584-56b01b2c1c75

Zhang, Ying, Liu, Wei and Wu, Hulin (2003) A simple nonparametric two-sample test for the distribution function of event time with interval censored data. Journal of Nonparametric Statistics, 15 (6), 643-652. (doi:10.1080/10485250310001624530).

Record type: Article

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.

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More information

Published date: 2003
Keywords: asymptotic normality, distribution function of event time, empirical estimate, interval censoring, Monte Carlo simulation, panel count data, pseudolikelihood estimate
Organisations: Statistics

Identifiers

Local EPrints ID: 30115
URI: http://eprints.soton.ac.uk/id/eprint/30115
ISSN: 1048-5252
PURE UUID: bad3dcaf-7505-4888-9fbb-b5428202314e
ORCID for Wei Liu: ORCID iD orcid.org/0000-0002-4719-0345

Catalogue record

Date deposited: 12 May 2006
Last modified: 16 Mar 2024 02:42

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Contributors

Author: Ying Zhang
Author: Wei Liu ORCID iD
Author: Hulin Wu

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