CHEBS provides training courses on the subject of Bayesian statistics in health care, and on Bayesian statistics in general.
Probabilistic Sensitivity Analysis: Part 1
The objective of these courses is to equip participants with the skills, technology and experience necessary to undertake probabilistic sensitivity analysis of cost-effectiveness models.
Part 1 deals with uncertainty in model inputs. Specifically, the course will show how to represent uncertainty about input parameters in cost-effectiveness models, making use of available published data and expert knowledge.
Particular attention will be paid to handling correlations between model parameters, and identifying and modelling 'data gaps': situations where there is a discrepancy between the parameters the data sources are informing us about and the parameters we need to specify in a cost-effectiveness model.
Probabilistic Sensitivity Analysis: Part 2
Part 2 deals with uncertainty in model outputs. Specifying probability distributions for all uncertain model inputs induces uncertainty in the output of the model. This course will show how to investigate and report this output uncertainty.
Particular attention will be paid to understanding the role of individual model input parameters in driving the output uncertainty.