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ullrika at the uncertainty show

Ullrika Sahlin

Senior lecturer

ullrika at the uncertainty show

A robust Bayesian model to quantify and adjust for study quality and conflict of interest in meta-analyses

Author

  • Matthias C.M. Troffaes
  • Lorenzo Casini
  • Jürgen Landes
  • Ullrika Sahlin

Summary, in English

Meta-analyses are vital for synthesizing evidence in medical research, but conflicts of interest can introduce research bias, undermining the reliability of the synthesized findings. This paper proposes a new robust Bayesian meta-analysis model. The model inflates uncertainty of low-quality studies and incorporates a bias term for studies subject to conflicts of interest. Using a random-effects model and sensitivity analysis with bounded probabilities, the model enables robust adjustments for conflicts of interest in meta-analytic contexts. A case study on antidepressant trials illustrates the potential application of the model.

Department/s

  • Centre for Environmental and Climate Science (CEC)
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • Computational Science for Health and Environment

Publishing year

2025

Language

English

Pages

273-284

Publication/Series

Proceedings of machine learning research

Volume

290

Document type

Preface to conference proceeding

Topic

  • Probability Theory and Statistics

Keywords

  • conflict of interest
  • meta-analysis
  • sensitivity analysis

Conference name

14th International Symposium on Imprecise Probabilities: Theories and Applications, ISIPTA 2025

Conference date

2025-07-15 - 2025-07-18

Conference place

Bielefeld, Germany

Status

Published

Research group

  • Computational Science for Health and Environment