… random effects in a linear mixed effects model. All give equivalent … Model fitting in mixed
effects models has been the subject of a large amount of research. In standard linear regression …

… analysis of continuous, hierarchical data using a different class of models, namely, linear
mixed-effects models … to the linear model (10.1)–(10.5), is defined by a linear combination of the …

… of linear mixed-effects (LME) models, introducing their basic concepts through the analysis of
several … To explore this potential linear relationship further, we fit separate linear regression …

… linear mixed-effects models can be determined using the lmer function in the lme4 package
for R. As for most model-fitting functions in R, the model … Just as a linear model is described …

… to mixed-effects modeling and a practical introduction to how to implement mixed-effects
models … These shortcomings of ANOVAs and multiple regression can be avoided by using linear …

… linear model methodology using R statistical software. Before setting off on this journey, it is
worth reviewing both linear models … Linear Model: We describe this data with a linear model …

… We generalize the well-known R2 measure for linear regression to linear mixed effects
models. Our work was motivated by a cluster-randomized study conducted by the Eastern …

… The results for linear regression models and linear mixed-effects models are the
continuous variable analog of this concept. If an interaction or higher order term is in the …

… regression coefficients are investigated in an exploratory manner. Another approach, we will
use in the paper, is to use a mixed effects model, … The following linear mixed effects model …

… Mixed-effects models are being used ever more frequently in the analysis of experimental
… standards for evaluating significance of fixed effects in these models (ie, obtaining p-values) …