Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools

Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools

Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools

Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools (Chapman & Hall/CRC Biostatistics Series)  by Marc Lavielle
Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects ModelsMixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework 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.
Easy-to-Use Techniques and Tools for Real-World Data ModelingThe book first shows how the framework allows model representation for different data types, including continuous, categorical, count, and time-to-event data. This leads to the use of generic methods, such as the stochastic approximation of the EM algorithm (SAEM), for modeling these diverse data types. The book also covers other essential methods, including Markov chain Monte Carlo (MCMC) and importance sampling techniques. The author uses publicly available software tools to illustrate modeling tasks. Methods are implemented in Monolix, and models are visually explored using Mlxplore and simulated using Simulx.
Ebook format: PDF
Ebook page: 380
File size: 12.40 MB

$48.00