Title

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

Authors

Authors

Y. Zhang; W. Liu;H. L. Wu

Comments

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Abbreviated Journal Title

J. Nonparametr. Stat.

Keywords

asymptotic normality; distribution function of event time; empirical; estimate; interval censoring; Monte Carlo simulation; panel count data; pseudolikelihood estimate; PROPORTIONAL HAZARDS MODEL; LINEAR RANK-TESTS; PANEL COUNT DATA; SURVIVAL-DATA; AIDS; INFERENCE; Statistics & Probability

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.

Journal Title

Journal of Nonparametric Statistics

Volume

15

Issue/Number

6

Publication Date

1-1-2003

Document Type

Article

DOI Link

http://dx.doi.org/10.1080/1048525310001624530

Language

English

First Page

643

Last Page

652

WOS Identifier

WOS:000188239800001

ISSN

1048-5252

Recommended Citation

"A simple nonparametric two-sample test for the distribution function of event time with interval censored data" (2003). Faculty Bibliography 2000s. 4154.
https://stars.library.ucf.edu/facultybib2000/4154