A version of the nonlinear mixed-effects model is presented that allows random effects only on the linear coefficients. Nonlinear parameters are not stochastic. In nonlinear regression, this kind of ...

Normality of random effects is a routine assumption for the linear mixed model, but it may be unrealistic, obscuring important features of among-individual variation. We relax this assumption by ...

Linear mixed models (LMMs) serve as a versatile statistical framework, combining fixed effects that capture the overall trends with random effects that account for variability across subjects ...

Limitations of linear regression applied on ecological data -- Things are not always linear : additive modeling -- Dealing with heterogeneity -- Mixed effects modeling for nested data -- Violation of ...