多吸收相型分布用于右删失竞争风险数据
Multi-Absorbing Phase-Type Distributions for Right-Censored Competing Risks Data
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中文总结 AI 辅助
本文提出多吸收相型分布用于竞争风险建模，开发EM算法处理右删失数据，并在重症监护数据上取得优于现有方法的似然值。
中文摘要 AI 辅助
相型（PH）分布是用于寿命时长的通用半参数模型，可应用于生存分析和可靠性分析。本文提出了在竞争风险模型中使用相型分布的方法和软件。由此产生的多吸收相型（MAPH）分布同时记录到达吸收状态的时间和原因。在阐述该分布族的基本性质后，我们开发了一种EM算法，用于从精确事件时间/原因观测和独立右删失观测中进行参数推断。对于删失个体，E步以生存至删失时间为条件，并同时推算其潜在瞬态路径和最终吸收原因；通过矩阵指数可获得闭式的原因分解充分统计量期望。我们展示了应用和数值性质，并描述了随附的两个Julia软件包，其中精确事件和删失E步均已实现。将该方法应用于重症监护住院时长数据（包括全部删失记录）时，所获得的似然值高于先前针对这些数据发表的相型竞争风险拟合结果。
英文摘要
Phase-type (PH) distributions are versatile semi-parametric models for lifetime duration and can be used in survival and reliability analysis. In this paper we put forward methods and software for using PH distributions in a competing-risks model. The resulting multi-absorbing phase-type (MAPH) distribution records both the time until absorption and its cause. After formulating basic properties of this family, we develop an EM algorithm for parameter inference from exact event-time/cause observations and independently right-censored observations. For a censored subject, the E-step conditions on survival up to the censoring time and imputes both the latent transient path and its eventual cause of absorption; closed-form cause-resolved sufficient-statistic expectations are obtained from matrix exponentials. We illustrate applications and numerical properties and describe two accompanying Julia packages, in which both the exact-event and the censored E-step are implemented. Applied to intensive-care length-of-stay data in full, censored records included, the method attains a higher likelihood than the phase-type competing-risks fit previously published for those data.
发表机构
- University of Queensland（昆士兰大学）
- Victoria University of Wellington（惠灵顿维多利亚大学）
- University of Auckland（奥克兰大学）
机构由 AI 辅助整理，请以论文原文为准。
