生物等效性数据分析。

IF 1.1 Q4 PHARMACOLOGY & PHARMACY

Translational and Clinical Pharmacology Pub Date : 2020-12-01 Epub Date: 2020-12-17 DOI:10.12793/tcp.2020.28.e20

Gowooni Park, Hyungsub Kim, Kyun-Seop Bae

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引用次数: 0

摘要

SAS®通常用于生物等效性(BE)数据分析。R是一款免费开放的通用数据分析软件，与SAS®相比，用于BE数据分析的频率较低。本教程解释了如何将R用于be数据分析，以生成与SAS®可比较的结果。BE数据分析的主要SAS®程序为PROC GLM和PROC MIXED，对应的R主程序包分别为“sasLM”和“nlme”。对于仅固定效应或平衡数据，SAS®PROC GLM和R“sasLM”提供了良好的估计;然而，对于具有不平衡数据的混合效应模型，SAS®PROC MIXED和R“nlme”在提供无偏倚估计方面更好。为了方便，提供了SAS®和R脚本。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Bioequivalence data analysis.

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Bioequivalence data analysis.

SAS^® is commonly used for bioequivalence (BE) data analysis. R is a free and open software for general purpose data analysis, and is less frequently used than SAS^® for BE data analysis. This tutorial explains how R can be used for BE data analysis to generate comparable results with SAS^®. The main SAS^® procedures for BE data analysis are PROC GLM and PROC MIXED, and the corresponding R main packages are "sasLM" and "nlme" respectively. For fixed effects only or balanced data, the SAS^® PROC GLM and R "sasLM" provide good estimates; however, for a mixed-effects model with unbalanced data, the SAS^® PROC MIXED and R "nlme" are better for providing estimates without bias. The SAS^® and R scripts are provided for convenience.

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来源期刊

Translational and Clinical Pharmacology Medicine-Pharmacology (medical)

CiteScore

1.60

自引率

11.10%

发文量

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.