Linear and non-linear mixed models

Linear and non-linear mixed models are statistical tools used for data with a hierarchical or clustered structure, but they differ in how they model the relationship between variables. A linear mixed model assumes the relationship is linear, while a non-linear mixed model allows for more complex, non-linear relationships between variables, either in the mean function or in how the random effects are specified. Both models include both fixed and random effects to account for population-level trends and subject-specific variations.