Mixed Effects Models for the Population Approach - Lavielle, Marc
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This book provides wide-ranging coverage of parametric modeling in linear and nonlinear mixed effects models. It presents a rigorous approach for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whole population of individuals at the same time. The book takes readers through the whole modeling process, from defining/creating a parametric model to performing tasks on the model using various mathematical methods. Numerous examples illustrate how to implement the models using the Monolix software.

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Produktbeschreibung
This book provides wide-ranging coverage of parametric modeling in linear and nonlinear mixed effects models. It presents a rigorous approach for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whole population of individuals at the same time. The book takes readers through the whole modeling process, from defining/creating a parametric model to performing tasks on the model using various mathematical methods. Numerous examples illustrate how to implement the models using the Monolix software.
Autorenporträt
Marc Lavielle is a statistician specializing in computational statistics and healthcare applications. He holds a Ph.D. in statistics from University Paris-Sud, Orsay. He was named professor at Paris Descartes University and joined Inria as research director in 2007. Creator of the Monolix software, he led the Monolix software development project at Inria between 2009 and 2011. He created the CNRS Research Group "Statistics and Health" in 2007. Since 2009, Dr. Lavielle has been a member of the French High Council of Biotechnologies, where he promotes the use of sound statistical methods to evaluate health and environmental risks related to genetically modified organisms (GMOs).