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

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.