Moumita Chatterjee, Sugata Sen Roy, Bhaswati Ganguli
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引用次数: 0
摘要
本文的动机是在交替复发事件的 Cox 比例危险模型中考虑受试者的具体变化。这是通过两组虚弱成分来实现的,这两组虚弱成分的边际分布由 copula 函数绑定在一起。似然函数涉及不可观测变量,因此需要使用 EM 算法。这就导致了难以解决的积分问题,在经过一些近似之后,需要使用计算密集型技术来解决。我们将结果应用于现实生活中的数据。此外,还进行了模拟研究,以检查一致性。
Modelling alternately recurring events using subject specific hazard estimation approach.
The motivation for this paper is to account for subject specific variations in a Cox proportional hazard model for alternating recurrent events. This is done through two sets of frailty components, whose marginal distributions are bound together by a copula function. The likelihood function involves unobservable variables, which requires the use of the EM algorithm. This leads to intractable integrals, which after some approximations, are solved using computationally intensive techniques. The results are applied to a real-life data. A simulation study is also carried out to check for consistency.
期刊介绍:
The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers:
Drug, device, and biological research and development;
Drug screening and drug design;
Assessment of pharmacological activity;
Pharmaceutical formulation and scale-up;
Preclinical safety assessment;
Bioavailability, bioequivalence, and pharmacokinetics;
Phase, I, II, and III clinical development including complex innovative designs;
Premarket approval assessment of clinical safety;
Postmarketing surveillance;
Big data and artificial intelligence and applications.