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Description
This module aims to provide a practical introduction to Bayesian analysis and Markov Chain Monte Carlo (MCMC) methods using the R statistical computing software environment and MCMC sampling software (such as BUGS or JAGS), as applied to cost-effectiveness analysis and the typical models used in health economic evaluations. It is primarily intended for third and fourth year undergraduates and taught postgraduates registered on the degree programmes offered by the Department of Statistical Science (including the MASS programmes). It also serves as an optional module for students from the MSc Health Economics and Decision Science degree. The academic prerequisite for all these students (in addition to their compulsory modules) is听STAT0008听辞谤 STAT0039.
Intended Learning Outcomes
- be able to听understand the basic concepts of Bayesian analysis;
- be able to听design, build, run and interpret the results of a Bayesian model, with specific application to health economic problems.
Applications - The skills taught in this module are widely transferrable to a variety of fields and applications, for example: medicine, public health, epidemiology and health services research.
Indicative Content - Introduction to health economic evaluations; Introduction to Bayesian inference; Introduction to MCMC in BUGS/JAGS; Analysis of cost and cost-utility data; Statistical cost-effectiveness analysis; Probabilistic Sensitivity Analysis (PSA); Evidence synthesis and hierarchical models; Decision-analytic and Markov models;听Monte Carlo estimation in BUGS; MCMC estimation in BUGS; Cost-effectiveness analysis with individual level data; Introduction to R and cost-effectiveness analysis using the R package BCEA; Health economic evaluation and PSA with R/BUGS/BCEA; Advanced topics in PSA in R using BCEA; Evidence synthesis (1): decision models; Evidence synthesis (2): network meta-analysis; Markov models in health economics.
Key Texts - Available from .
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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