Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects
Models Mixed Effects Models for the Population Approach: Models, Tasks, Methods and …

It has been an amazing time since the publication of the first edition, with vast changes
taking place in the fields of mixed effects models and their applications. At the time when the …

Mixed modelling is very useful, and easier than you think! Mixed modelling is now well
established as a powerful approach to statistical data analysis. It is based on the recognition …

Many common statistical models can be expressed as linear models that incorporate both
fixed effects, which are parameters associated with an entire population or with certain …

Highly recommended by JASA, Technometrics, and other leading statistical journals, the first
two editions of this bestseller showed how to easily perform complex linear mixed model …

Mixed effects models have become very popular, especially for the analysis of longitudinal
data. One challenge is how to build a good enough mixed effects model. In this paper, we …

An overview of the theory and application of linear and nonlinear mixed-effects models in
the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel …

This new edition of the successful multi-disciplinary text Statistical Modelling in GLIM takes
into account new developments in both statistical software and statistical modeling …

Statistical models provide a framework in which to describe the biological process giving
rise to the data of interest. The construction of this model requires balancing adequate …

This Tutorial serves as both an approachable theoretical introduction to mixed-effects
modeling and a practical introduction to how to implement mixed-effects models in R. The …