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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/50388

    Title: Analysis of two-sample censored data using a semiparametric mixture model
    Authors: Li, Gang;林千代;Lin, Chien-tai
    Contributors: 淡江大學數學學系
    Keywords: Biased sampling;EM algorithm;maximum likelihood estimation;mixture model;semiparametric model
    Date: 2009-07
    Issue Date: 2010-08-09 16:41:54 (UTC+8)
    Publisher: Springer
    Abstract: In this article we study a semiparametric mixture model for the two-sample problem with right censored data. The model implies that the densities for the continuous outcomes are related by a parametric tilt but otherwise unspecified. It provides a useful alternative to the Cox (1972) proportional hazards model for the comparison of treatments based on right censored survival data. We propose an iterative algorithm for the semiparametric maximum likelihood estimates of the parametric and nonparametric components of the model. The performance of the proposed method is studied using simulation. We illustrate our method in an application to melanoma.
    Relation: Acta Mathematicae Applicatae Sinica, English Series 25(3), pp.389-398
    DOI: 10.1007/s10255-008-8804-4
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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