Non-parametric maximum-likelihood estimation in a semiparametric mixture model for competing-risks data

作者：Chang I Shou^*; Hsiung Chao A; Wen Chi Chung; Wu Yuh Jenn; Yang Che Chi

来源：Scandinavian Journal of Statistics, 2007, 34(4): 870-895.

DOI：10.1111/j.1467-9469.2007.00567.x

• case fatality rate
• competing-risks problems
• self-consistency equation
• severe acute respiratory syndrome

This paper describes our studies on non-parametric maximum-likelihood estimators in a semiparametric mixture model for competing-risks data, in which proportional hazards models are specified for failure time models conditional on cause and a multinomial model is specified for the marginal distribution of cause conditional on covariates. We provide a verifiable identifiability condition and, based on it, establish an asymptotic profile likelihood theory for this model. We also provide efficient algorithms for the computation of the non-parametric maximum-likelihood estimate and its asymptotic variance. The success of this method is demonstrated in simulation studies and in the analysis of Taiwan severe acute respiratory syndrome data.

• 出版日期2007-12