Goodness-of-fit test for hazard rate. Issue 2 (2nd April 2020)

• Record Type: Journal Article
• Authors: Vital, Ralph-Antoine; Patil, Prakash
• Is Part Of: Journal of nonparametric statistics. Volume 32:Issue 2(2020)
• Page Start: 403
• Page End: 427
• Publication Date: 2020-04-02
• Subjects: Goodness-of-fit test -- hazard rate -- local alternatives -- Pitman alternatives -- power of the test -- smoothing parameter; Nonparametric statistics -- Periodicals; 519.5
• DOI: 10.1080/10485252.2020.1758317
• Languages: English
• ISSNs: 1048-5252

Abstract

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 N β, β < 1 / 2, where N is the sample size.