一类地点尺度检验的鞍点 p 值。

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Abd El-Raheem M Abd El-Raheem, Haidy N Mohamed, Ehab F Abd-Elfattah
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引用次数: 0

摘要

本文的主要思想是近似计算一类非参数双样本位置标度检验的精确 p 值。本文将最著名的非参数双样本位置标度检验归结为一类线性秩检验。该类检验的置换分布来自随机分配设计。因此,我们可以利用鞍点近似法近似得到该类非参数双样本位置标度检验的精确 p 值。与正态近似法相比,所提出的方法在近似精确 p 值方面具有很高的准确性。此外,与模拟方法一样,拟议方法只需要少量计算和时间。通过四组真实数据(代表多个不同领域的应用),阐明了拟议方法的程序。此外,模拟研究比较了建议的方法和传统方法,以逼近非参数双样本位置尺度检验指定类别的精确 p 值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Saddlepoint p-values for a class of location-scale tests.

The main idea of this paper is to approximate the exact p-value of a class of non-parametric, two-sample location-scale tests. In this paper, the most famous non-parametric two-sample location-scale tests are formulated in a class of linear rank tests. The permutation distribution of this class is derived from a random allocation design. This allows us to approximate the exact p-value of the non-parametric two-sample location-scale tests of the considered class using the saddlepoint approximation method. The proposed method shows high accuracy in approximating the exact p-value compared to the normal approximation method. Moreover, the proposed method only requires a few calculations and time, as in the case of the simulated method. The procedures of the proposed method are clarified through four sets of real data that represent applications for a number of different fields. In addition, a simulation study compares the proposed method with the traditional methods to approximate the exact p-value of the specified class of the non-parametric two-sample location-scale tests.

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来源期刊
Journal of Biopharmaceutical Statistics
Journal of Biopharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.50
自引率
18.20%
发文量
71
审稿时长
6-12 weeks
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.
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