采用分层或不分层的Miettinen-Nurminen评分法。

IF 1.1 Q4 PHARMACOLOGY & PHARMACY Translational and Clinical Pharmacology Pub Date : 2022-09-01 Epub Date: 2022-09-26 DOI:10.12793/tcp.2022.30.e16
Moon Hee Lee, Kyun-Seop Bae
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引用次数: 0

摘要

临床数据2 × 2表的分析包括计算风险差异、相对风险或优势比的点估计和置信区间。虽然这些比较参数的点估计是唯一定义的,但已经提出了几种统计方法来估计每个参数的置信区间。Miettinen-Nurminen (MN)评分法有望取代传统的区间估计方法得到越来越多的应用。在R软件中,对于分层数据,MN评分方法以前没有实现过。需要一个全面的软件来实现MN计分法。本文介绍了在sasLM R软件包中MN计分法的实现。为了演示所介绍的sasLM功能的使用,以最近发表的临床数据为例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Implementation of Miettinen-Nurminen score method with or without stratification in R.

Analysis of a 2 × 2 table for clinical data involves computing the point estimate and confidence interval for risk difference, relative risk, or odds ratio. While point estimates of these comparative parameters are uniquely defined, several statistical methods have been proposed to estimate the confidence interval for each parameter. The Miettinen-Nurminen (MN) score method is expected to be used increasingly over traditional interval estimation methods. The MN score method has not been previously implemented in R software for data with stratification. There is a need for a comprehensive software implementation of the MN score method. This article describes the implementation of the MN score method in the sasLM R software package. To demonstrate the usage of the sasLM functions introduced, recently published clinical data are provided as examples.

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来源期刊
Translational and Clinical Pharmacology
Translational and Clinical Pharmacology Medicine-Pharmacology (medical)
CiteScore
1.60
自引率
11.10%
发文量
17
期刊介绍: Translational and Clinical Pharmacology (Transl Clin Pharmacol, TCP) is the official journal of the Korean Society for Clinical Pharmacology and Therapeutics (KSCPT). TCP is an interdisciplinary journal devoted to the dissemination of knowledge relating to all aspects of translational and clinical pharmacology. The categories for publication include pharmacokinetics (PK) and drug disposition, drug metabolism, pharmacodynamics (PD), clinical trials and design issues, pharmacogenomics and pharmacogenetics, pharmacometrics, pharmacoepidemiology, pharmacovigilence, and human pharmacology. Studies involving animal models, pharmacological characterization, and clinical trials are appropriate for consideration.
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