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Multivariate Failure Time Analysis when only the Time to First Failure is Observed

机译:仅观察首次失效时间时的多元失效时间分析

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摘要

We propose a log-linear mixed model to assess covariate effects on the unobservable, catheter-related time-until-infection (TUI), utilizing the observable time-until-first-infection (TUFI). The model assumes that both log (TUI) and the common (random) patient effect follow an extreme value distribution, and TUIs of the same patient are conditionally independent. This model enables the assessment of covariate effects on TUI, accounting for both patient-level (age) and catheter-level (e.g., difficulty of insertion) covariates and the within-patient correlation. The efficient likelihood estimators of fixed-effects and scale parameters of random effects are shown to be consistent and asymptotically normal and appear to perform well in simulations. The methods are illustrated using an example.
机译:我们提出了一个对数线性混合模型,以利用可观察到的直到第一时间的感染(TUFI)来评估对不可观察到的,与导管相关的直到感染的时间(TUI)的协变量影响。该模型假设对数(TUI)和普通(随机)患者影响均遵循极值分布,并且同一患者的TUI在条件上独立。该模型能够评估对TUI的协变量影响,同时考虑患者水平(年龄)和导管水平(例如,插入困难)的协变量以及患者内部的相关性。固定效应的有效似然估计器和随机效应的尺度参数被证明是一致且渐近正态的,并且在模拟中表现良好。通过示例说明了这些方法。

著录项

  • 来源
  • 作者

    Steven Y. Hua;

  • 作者单位

    Pfizer Research, Cambridge, Massachusetts, USA;

    Department of Mathematics, University of Texas at Arlington, Arlington, Texas, USA;

    Department of Biostatistics, University of North Carolina at Chapel Hill, North Carolina, USA;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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