Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ioannidis JPA. Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses. Can Med Assoc J. 2009;181(8):488–93.
Sutton AJ, Abrams KR. Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res. 2001;10:277–303.
Vázquez-Polo FJ, Moreno E, Negrín MA, Martel M. A Bayesian sensitivity study of risk difference in the meta-analysis of binary outcomes from sparse data. Expert Rev Pharmacoecon Outcomes Res. 2015;15(2):317–22.
Lambert PC, Sutton AJ, Burton PR, Abrams KR, Jones DR. How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS. Stat Med. 2005;24:2401–28.
Moreno E, Vázquez-Polo FJ, Negrín MA. Objective Bayesian meta-analysis for sparse discrete data. Stat Med. 2014;33:3676–92.
Acknowledgements
This work was partially supported by grant ECO2013-47092 (Ministerio de Economía y Competitividad, Spain).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Polo, F.J.V., Negrín, M.A., Martel, M. (2016). Bayesian Approach to Evidence Synthesis. In: Biondi-Zoccai, G. (eds) Umbrella Reviews. Springer, Cham. https://doi.org/10.1007/978-3-319-25655-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-25655-9_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25653-5
Online ISBN: 978-3-319-25655-9
eBook Packages: MedicineMedicine (R0)