Abstract

Provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data. This book also presents an unified model-building strategy for both linear and nonlinear models, applying it to the analysis of over 20 real datasets from areas including pharmacokinetics, agriculture and manufacturing.

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