Open Access
June 2009 New multi-sample nonparametric tests for panel count data
N. Balakrishnan, Xingqiu Zhao
Ann. Statist. 37(3): 1112-1149 (June 2009). DOI: 10.1214/08-AOS599


This paper considers the problem of multi-sample nonparametric comparison of counting processes with panel count data, which arise naturally when recurrent events are considered. Such data frequently occur in medical follow-up studies and reliability experiments, for example. For the problem considered, we construct two new classes of nonparametric test statistics based on the accumulated weighted differences between the rates of increase of the estimated mean functions of the counting processes over observation times, wherein the nonparametric maximum likelihood approach is used to estimate the mean function instead of the nonparametric maximum pseudo-likelihood. The asymptotic distributions of the proposed statistics are derived and their finite-sample properties are examined through Monte Carlo simulations. The simulation results show that the proposed methods work quite well and are more powerful than the existing test procedures. Two real data sets are analyzed and presented as illustrative examples.


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N. Balakrishnan. Xingqiu Zhao. "New multi-sample nonparametric tests for panel count data." Ann. Statist. 37 (3) 1112 - 1149, June 2009.


Published: June 2009
First available in Project Euclid: 10 April 2009

zbMATH: 1160.62037
MathSciNet: MR2509069
Digital Object Identifier: 10.1214/08-AOS599

Primary: 62G10
Secondary: 62G20

Keywords: counting processes , medical follow-up study , nonparametric comparison , Nonparametric maximum likelihood , nonparametric maximum pseudo-likelihood , panel count data

Rights: Copyright © 2009 Institute of Mathematical Statistics

Vol.37 • No. 3 • June 2009
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