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Applying Historical Data in a Nonlinear Mixed-Effects Model Can Reduce the Number of Control Rats Required for Calculation of The Relative Potency of Insulin Analogues
View ORCID ProfileEmilie Prang Nielsen, Søren Andersen, Christian Lehn Brand, Susanne Ditlevsen
doi: https://doi.org/10.1101/2021.09.10.459831
Emilie Prang Nielsen
1University of Copenhagen, Biostatistics
Søren Andersen
2Novo Nordisk A/S Gobal Research, Biostatistics
Christian Lehn Brand
3Novo Nordisk AS Gobal Research, Diabetes Pharmacology
Susanne Ditlevsen
4University of Copenhagen, Data Science Laboratory, Mathematical Sciences

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Posted September 10, 2021.
Applying Historical Data in a Nonlinear Mixed-Effects Model Can Reduce the Number of Control Rats Required for Calculation of The Relative Potency of Insulin Analogues
Emilie Prang Nielsen, Søren Andersen, Christian Lehn Brand, Susanne Ditlevsen
bioRxiv 2021.09.10.459831; doi: https://doi.org/10.1101/2021.09.10.459831
Applying Historical Data in a Nonlinear Mixed-Effects Model Can Reduce the Number of Control Rats Required for Calculation of The Relative Potency of Insulin Analogues
Emilie Prang Nielsen, Søren Andersen, Christian Lehn Brand, Susanne Ditlevsen
bioRxiv 2021.09.10.459831; doi: https://doi.org/10.1101/2021.09.10.459831
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