分层单侧和双侧数据的共同风险差异区间估计✩。

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Shuman Sun, Zhiming Li, Keyi Mou
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引用次数: 0

摘要

在临床试验中,如果受试者提供一个或两个成对器官的数据,通常会遇到单侧或双侧数据。对于双侧数据,来自两个成对身体部位的反应是相关的。本文基于 Dallal 模型,研究了分层单侧和双侧数据中常见风险差异的各种置信区间。仿真结果表明,得分法优于其他方法,其覆盖概率接近标称水平,覆盖宽度也令人满意。因此,该方法值得推荐。此外,随着样本量的增加,反双曲正切 Wald 型与分数法一样成为最优方法。本文以耳鼻喉科为例演示了所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interval estimation of common risk difference for stratified unilateral and bilateral data✩.

In clinical trials, unilateral or bilateral data can usually be encountered if a subject contributes one or both of paired organs. For the bilateral data, responses from two paired body parts are correlated. In this paper, we study various confidence intervals of common risk difference in stratified unilateral and bilateral data based on the Dallal's model. Simulation results show that the score method outperforms other methods and provides coverage probability close to the nominal level and satisfactory coverage width. Hence, the method is recommended. In addition, the inverse hyperbolic tangent Wald-type become as optimal as the score method with the increase of sample sizes. An otolaryngology example is used to demonstrate the proposed methods.

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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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