Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Park, Gowooni, Kim, Hyungsub, Bae, Kyun-Seop
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Clinical Pharmacology and Therapeutics 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781810/
https://www.ncbi.nlm.nih.gov/pubmed/33425800
http://dx.doi.org/10.12793/tcp.2020.28.e20
Descripción
Sumario: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.