The Standard Output: A Tool‐Agnostic Modeling Storage Format

• Published in: CPT: pharmacometrics and systems pharmacology Vol. 7; no. 9; pp. 543 - 546
• Main Authors: Terranova, Nadia, Smith, Mike K., Nordgren, Rikard, Comets, Emmanuelle, Lavielle, Marc, Harling, Kajsa, Hooker, Andrew C., Sarr, Celine, Mentré, France, Yvon, Florent, Swat, Maciej J.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.09.2018; John Wiley and Sons Inc; Wiley
• Subjects: Collaboration; Design optimization; Economic models; Information retrieval; Interoperability; Libraries; Population; Reproducibility; Simulation; Software; Software upgrading
• ISSN: 2163-8306; 2163-8306
• DOI: 10.1002/psp4.12339

The SO is based on a hierarchical structure defined to separate independent output information or results obtained from different modeling tasks (e.g., estimation, simulation, and optimal design), whereas standardizing and providing consistent definition of output structure from different estimation methods and tools (e.g., for maximum likelihood and stochastic or sample-based estimation). AIC, Akaike information criterion; BIC, Bayesian information criteria; CI, confidence interval; DIC, Deviance Information Criterion; FIM, Fisher Information Matrix; MLE, maximum likelihood estimation; OF, Objective Function; PDF, probability density function VPC, Visual Predictive Check. [...]the element contains the values of various estimated objective function measures, such as the likelihood, log-likelihood, tool-specific objective function, deviance, and individual contributions to likelihood, as well as the calculated values of the most common information criteria used for model selection purpose (i.e., Akaike information criterion, Bayesian information criteria, and Deviance Information Criterion). [...]any level below (e.g., occasion) or above (e.g., country or center) the subject level can be considered.