Ullrika Sahlin
Senior lecturer
A robust Bayesian model to quantify and adjust for study quality and conflict of interest in meta-analyses
Author
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