Advanced Decision Science Methods and Modeling in Health

Catalog description

Advanced methods currently used in published model-based cost-effectiveness analyses in medicine and public health, both theory and technical applications. Topics include Markov, differential equation, microsimulation, and discrete-event simulation (DES) models, model calibration and evaluation, input parameter estimation, deterministic and probabilistic sensitivity analyses, and value of information analysis. Prerequisites: a course in probability theory, a course in calculus, a course in statistics or biostatistics, a course on cost-effectiveness such as HRP 392, a course in economics, and familiarity with programming languages such as R or Python.