In real-life dataset, often the variables are correlated based on their inherent mutual association. For example, patients from several suburbs of the same city are selected. Often multiple cities from the same state or province are selected. Patients belonging to the same suburb or city includes same local-level or state-level characteristics. In such situations when we use regression models, we often need to use multilevel models. Multilevel models, also known as hierarchical models, nested models. It is designed to explore and analyse data that comes from populations which have a complex structure.