Tests for cured proportion for recurrent event count data when the data are censored

K. Sumathi, K. Aruna Rao

Research output: Contribution to journalArticle

Abstract

Sumathi and Rao (2008) proposed a cure model for recurrent event count data. The proposed model was based on the zero inflated Poisson (ZIP) distribution. Several tests were proposed for testing the cured proportion when the data set is uncensored (Sumathi and Rao, 2010). But in long term follow up studies, the investigators very often come across situations where the patients are lost to follow up and the data sets are said to be censored. The present paper is an extension of the work of Sumathi and Rao (2010). In the present paper, tests are proposed for testing the cured proportion in a randomly censored recurrent event count data. The small sample performances of the proposed tests are studied using simulations.

Original languageEnglish
Pages (from-to)163-182
Number of pages20
JournalSouth African Statistical Journal
Volume47
Issue number2
Publication statusPublished - 25-11-2013

Fingerprint

Recurrent Events
Count Data
Proportion
Cure Model
Zero Distribution
Testing
Poisson distribution
Small Sample
Term
Count data
Simulation
Model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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Tests for cured proportion for recurrent event count data when the data are censored. / Sumathi, K.; Aruna Rao, K.

In: South African Statistical Journal, Vol. 47, No. 2, 25.11.2013, p. 163-182.

Research output: Contribution to journalArticle

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