Data may present several levels of variability (individual, geographic ?). To analyse this type of data and extract the maximum of information, it is necessary to take into account different sources of variability in the model. Hierarchical models (generalizing mixed models) are able to take into account the hierarchical structure of data when estimating parameters. This course will present the different steps needed to model hierarchical data; a particular attention will be paid to the choice of prior distribution and the procedure maximizing parameters estimation. This course will allow students to get used to hierarchical models through appropriate examples from public health.

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3