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 ...

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, ...

It is traditionally assumed that the random effects in mixed models follow a multivariate normal distribution, making likelihood-based inferences more feasible theoretically and computationally.