Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools (Chapman & Hall/CRC Biostatistics Series)
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| Title | : | Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools (Chapman & Hall/CRC Biostatistics Series) |
| Author | : | |
| Rating | : | 4.98 (833 Votes) |
| Asin | : | 1482226502 |
| Format Type | : | Hardcover |
| Number of Pages | : | 383 Pages |
| Publish Date | : | 2014-07-14 |
| Genre | : |
Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects Models
Mixed 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 Modeling
The 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 modeli
Editorial : "Although there are many excellent books available on mixed linear models and generalized linear mixed models, few provide broad coverage of nonlinear models. The strength of this text is the extensive coverage of the modeling of nonlinear trajectories in a wide variety of forms." (Journal of the American Statistical Association)
"… the text contains much of interest to the applied statistician who may be working as a consultant. … I found the text useful to explain the difference between individual and population models so I have no hesitation in recommending this book for applied statisticians who may need a few well-developed examples from which to explain, and explore, statistical concepts and hierarchical modeling with non-statistical clients. In addition to model formulation and parameter estimation, the author addresses topics in model selection and diagnostic tools, too. … a valuable text that is well-worth reading …"
International St
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