We briefly present the advantages and opportunities available to umbrella reviews from the use of Bayesian techniques while taking into account that the concerns commonly arising in Bayesian meta-analysis procedures are also present in umbrella reviews. This is the case, for example, of sparse data, for which the hierarchical logit-normal model can give very poor results. An additional concern in this context is that of the choice of noninformative priors, which can lead to a significant variation in the final conclusions drawn. Accordingly, this chapter highlights the potential for Bayesian approaches in umbrella reviews, overviews of reviews, and meta-epidemiologic studies while acknowledging their limitations and complexities.
CITATION STYLE
Polo, F. J. V., Negrín, M. A., & Martel, M. (2016). Bayesian approach to evidence synthesis. In Umbrella Reviews: Evidence Synthesis with Overviews of Reviews and Meta-Epidemiologic Studies (pp. 155–160). Springer International Publishing. https://doi.org/10.1007/978-3-319-25655-9_11
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