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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

Emilie Prang Nielsen, Søren Andersen, Christian Lehn Brand, Susanne Ditlevsen
doi: https://doi.org/10.1101/2021.09.10.459831

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doi 
https://doi.org/10.1101/2021.09.10.459831
History 
  • September 10, 2021.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

Author Information

  1. Emilie Prang Nielsen1,*,
  2. Søren Andersen2,
  3. Christian Lehn Brand3 and
  4. Susanne Ditlevsen4
  1. 1University of Copenhagen, Biostatistics
  2. 2Novo Nordisk A/S Gobal Research, Biostatistics
  3. 3Novo Nordisk AS Gobal Research, Diabetes Pharmacology
  4. 4University of Copenhagen, Data Science Laboratory, Mathematical Sciences
  1. ↵* Corresponding author; email: emilie.nielsen{at}hotmail.com
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Posted September 10, 2021.
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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
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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