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Bioequivalence data analysis

Translational and Clinical Pharmacology 2020년 28권 4호 p.175 ~ 180
Park Gowooni, 김형섭, 배균섭,
소속 상세정보
 ( Park Gowooni ) - University of Ulsan College of Medicine Asan Medical Center Department of Clinical Pharmacology and Therapeutics
김형섭 ( Kim Hyung-Sub ) - University of Ulsan College of Medicine Asan Medical Center Department of Clinical Pharmacology and Therapeutics
배균섭 ( Bae Kyun-Seop ) - University of Ulsan College of Medicine Asan Medical Center Department of Clinical Pharmacology and Therapeutics

Abstract


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.

키워드

SAS®; GLM; MIXED; sasLM; nlme

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