Introduction to Bayesian modelling in dental research

Objective To explain the concepts and application of Bayesian modelling and how it can be applied to the analysis of dental research data. Basic desig n Methodological in nature, this article introduces Bayesian modelling thro ugh hypothetical dental examples. Setting The synthesis of RCT results with previous evidence, including expert opinion, is used to illustrate full Ba yesian modelling. Meta-analysis, in the form of empirical Bayesian modellin g, is introduced. An example of full Bayesian modelling is described for th e synthesis of evidence from several studies that investigate the success o f root canal treatment. Hierarchical (Bayesian) modelling is demonstrated f or a survey of childhood caries, where surface data is nested within subjec ts. Results Bayesian methods enhance interpretation of research evidence th rough the synthesis of information from multiple sources. Conclusions Bayes ian modelling is now readily accessible to clinical researchers and is able to augment the application of clinical decision making in the development of guidelines and clinical practice.