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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society for Clinical Pharmacology and Therapeutics
2020
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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 |
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. |
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