Cure rate model with bivariate interval censored data. Issue 9 (21st October 2017)

• Record Type: Journal Article
• Authors: Kim, Yang-Jin
• Is Part Of: Communications in statistics. Volume 46:Issue 9(2017)
• Page Start: 7116
• Page End: 7124
• Publication Date: 2017-10-21
• Subjects: Association -- Bivariate interval censored data -- Copula -- Cure rate model -- ES algorithm -- Pseudo-likelihood; 62JPP -- 62P10; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2016.1228959
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: A mixture model is proposed to analyze a bivariate interval censored data with cure rates. There exist two types of association related with bivariate failure times and bivariate cure rates, respectively. A correlation coefficient is adopted for the association of bivariate cure rates and a copula function is applied for bivariate survival times. The conditional expectation of unknown quantities attributable to interval censored data and cure rates are calculated in the E-step in ES (Expectation-Solving algorithm) and the marginal estimates and the association measures are estimated in the S-step through a two-stage procedure. A simulation study is performed to evaluate the suggested method and a real data from HIV patients is analyzed as a real data example.