Bayesian analysis

Bayesian analysis is a statistical inference approach where data are collected to refine the estimate of a particular quantity (often a probability) that may be used for decision making. This contracts with frequentist statistics, where data are collected to confirm/reject a null hypothesis. Bayesian techniques synthesise prior knowledge of a parameter with new study data to estimate a posterior distribution for that parameter. While the principle of Bayesian inference was first proposed by Rev. Thomas Bayes in the 1700s, widespread application became feasible in the 1980s with advancements in computing and computational methods. In healthcare evaluation, Bayesian analysis is most commonly used in network meta-analysis and aspects of (adaptive) trial design. It can be argued that economic modelling and decision analysis is often Bayesian in its approach.