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Research ArticleResearch

Models for Counts and Particle Size Distributions of Subvisible Particle Data

Jorge Quiroz, Elsa M. Vazquez, Jeffrey Wilson, Anita Dabbara and Jason K. Cheung
PDA Journal of Pharmaceutical Science and Technology May 2021, 75 (3) 213-229; DOI: https://doi.org/10.5731/pdajpst.2020.011510
Jorge Quiroz
1Research CMC Statistics, Merck & Co., Inc., Kenilworth, NJ;
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  • For correspondence: jorge.quiroz@merck.com
Elsa M. Vazquez
2Arizona State University, Tempe, AZ; and
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Jeffrey Wilson
2Arizona State University, Tempe, AZ; and
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Anita Dabbara
3Pharmaceutical Sciences, Merck & Co., Inc., Kenilworth, NJ
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Jason K. Cheung
3Pharmaceutical Sciences, Merck & Co., Inc., Kenilworth, NJ
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  • Article
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PDA Journal of Pharmaceutical Science and Technology: 75 (3)
PDA Journal of Pharmaceutical Science and Technology
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Models for Counts and Particle Size Distributions of Subvisible Particle Data
Jorge Quiroz, Elsa M. Vazquez, Jeffrey Wilson, Anita Dabbara, Jason K. Cheung
PDA Journal of Pharmaceutical Science and Technology May 2021, 75 (3) 213-229; DOI: 10.5731/pdajpst.2020.011510

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Models for Counts and Particle Size Distributions of Subvisible Particle Data
Jorge Quiroz, Elsa M. Vazquez, Jeffrey Wilson, Anita Dabbara, Jason K. Cheung
PDA Journal of Pharmaceutical Science and Technology May 2021, 75 (3) 213-229; DOI: 10.5731/pdajpst.2020.011510
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  • Article
    • Abstract
    • 1. Introduction
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Keywords

  • Generalized linear mixed models
  • Poisson regression with normal random effects
  • Ordinal logistic regression with normal random effects models
  • Overdispersion

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