Overview
Teaching Methods
-
Four modules together with introductory, policy context and closing sections
-
‘Bite-size’ video presentations from members of the Faculty for each module
-
Computer-based exercises using MS Excel
-
*NEW* Alternative ‘R’-based exercise track for those already familiar with R
-
Video ‘run-through’ of each exercise by members of the Faculty
-
Online discussion forums monitored by Faculty and tutors
-
One ‘live’ question and answer session for each module with module leads
How It Works
Course Dates
Objectives
By the end of the course, participants will be able to:
-
Model and populate a Markov model with time-dependent probabilities based on the results of parametric survival modelling
-
Develop a probabilistic model to reflect parameter uncertainty and to run Monte Carlo simulation
-
Present the results of a probabilistic model using net monetary benefits and cost-effectiveness acceptability curves
-
Assess the expected value of perfect information
Prerequisites
Faculty

Course Lead Andrew Briggs

Module Lead Karl Claxton

Module Lead Stephen Palmer

Module Lead Claire Rothery

Course Lead Mark Sculpher

Module Lead Alec Miners

R Tutor Lead Nichola Naylor
