Advertisement

Bayesian Approach to Evidence Synthesis

Chapter
  • 1.2k Downloads

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.

Keywords

Bayesian statistics Intrinsic priors Link distribution Meta-analysis Umbrella review 

Notes

Acknowledgements

This work was partially supported by grant ECO2013-47092 (Ministerio de Economía y Competitividad, Spain).

References

  1. 1.
    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.CrossRefGoogle Scholar
  2. 2.
    Sutton AJ, Abrams KR. Bayesian methods in meta-analysis and evidence synthesis. Stat Methods Med Res. 2001;10:277–303.CrossRefPubMedGoogle Scholar
  3. 3.
    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.CrossRefPubMedGoogle Scholar
  4. 4.
    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.CrossRefPubMedGoogle Scholar
  5. 5.
    Moreno E, Vázquez-Polo FJ, Negrín MA. Objective Bayesian meta-analysis for sparse discrete data. Stat Med. 2014;33:3676–92.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Quantitative Methods and TiDES InstituteUniversity of Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain

Personalised recommendations