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

    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

    Language

    English

    First Page

    643

    Last Page

    652

    WOS Identifier

    WOS:000188239800001

    ISSN

    1048-5252

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