Linear Mixed-Effect Models

Linear Mixed-Effect Modelling is an approach complimentary to other classes of linear models such as General Linear Models and Generalized Linear Models.

This website contains reference examples of Linear Mixed-Effect Models (LMMs or just MMs for short) otherwise known as Hierarchical Linear Models (HLMs) or Multi Level Models. Used when the assumption of independence is broken and General Linear Models are no longer appropriate (they do a pretty reasonable job though as a little aside in Example #2 shows). Independence is broken when same samples are measured multiple times (time course e.g. when alcohol use is measured each year within a fixed group of subjects) or when samples are correlated (e.g. family members are likely not independent with respect to religious faith).