國家衛生研究院 NHRI:Item 3990099045/1752
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    題名: Non-parametric maximum-likelihood estimation in a semiparametric mixture model for competing-risks data
    作者: Chang, IS;Hsiung, CA;Wen, CC;Wu, YJ;Yang, CC
    貢獻者: Division of Biostatistics and Bioinformatics;National Institute of Cancer Research
    摘要: 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.
    關鍵詞: Statistics & Probability
    日期: 2007-12
    關聯: Scandinavian Journal of Statistics. 2007 Dec;34(4):870-895.
    Link to: http://dx.doi.org/10.1111/j.1467-9469.2007.00567.x
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0303-6898&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000251329800010
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=36749102614
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