ABSTRACT In Pharmacokinetic (PK) and Pharmacodynamic (PD), the hazard rate functions play a central role in modelling time-to-event data. In the context of assessing the appropriateness of a given parametric hazard model, Huh, Y., and Hutmacher, M. [(2016), ‘Application of a Hazard-based Visual Predictive Check to Evaluate Parametric Hazard Models’, Journal of Pharmacokinetics and Pharmacodynamics, 43, 57–71] showed that a hazard-based visual predictive check is as good as a visual predictive check based on the survival function. However, for the lack of objectivity of such a visual method in this paper, we propose a nonparametric goodness-of-fit test for hazard rate functions. Besides having good power properties against the fixed alternatives, the proposed nonparametric kernel-based test also can detect alternatives converging to the null at the rate of where N is the sample size.

中文翻译：

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危险率的拟合优度检验

摘要 在药代动力学 (PK) 和药效学 (PD) 中，危险率函数在事件时间数据建模中发挥着核心作用。在评估给定参数危害模型的适当性的背景下，Huh, Y. 和 Hutmacher, M. [（2016 年），“基于危害的视觉预测检查评估参数危害模型的应用”，药代动力学杂志和Pharmacodynamics, 43, 57–71] 表明基于危害的视觉预测检查与基于生存函数的视觉预测检查一样好。然而，由于本文中这种视觉方法缺乏客观性，我们提出了一种风险率函数的非参数拟合优度检验。除了对固定替代品具有良好的功率特性外，