A robust Bayesian model to quantify and adjust for study quality and conflict of interest in meta-analyses
Troffaes, Matthias C.M. ; Casini, Lorenzo ; Landes, Jürgen and Sahlin, Ullrika LU
(2025)
14th International Symposium on Imprecise Probabilities: Theories and Applications, ISIPTA 2025
290.
p.273-284
- Abstract
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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/0eb74e24-25be-4725-90f7-ae4931061d81
- author
- Troffaes, Matthias C.M.
; Casini, Lorenzo
; Landes, Jürgen
and Sahlin, Ullrika
LU
- organization
- publishing date
- 2025
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- conflict of interest, meta-analysis, sensitivity analysis
- host publication
- Proceedings of Machine Learning Research
- volume
- 290
- pages
- 12 pages
- conference name
- 14th International Symposium on Imprecise Probabilities: Theories and Applications, ISIPTA 2025
- conference location
- Bielefeld, Germany
- conference dates
- 2025-07-15 - 2025-07-18
- external identifiers
-
- scopus:105014392330
- language
- English
- LU publication?
- yes
- id
- 0eb74e24-25be-4725-90f7-ae4931061d81
- date added to LUP
- 2025-11-17 11:59:15
- date last changed
- 2025-11-17 11:59:54
@misc{0eb74e24-25be-4725-90f7-ae4931061d81,
abstract = {{<p>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.</p>}},
author = {{Troffaes, Matthias C.M. and Casini, Lorenzo and Landes, Jürgen and Sahlin, Ullrika}},
booktitle = {{Proceedings of Machine Learning Research}},
keywords = {{conflict of interest; meta-analysis; sensitivity analysis}},
language = {{eng}},
pages = {{273--284}},
title = {{A robust Bayesian model to quantify and adjust for study quality and conflict of interest in meta-analyses}},
volume = {{290}},
year = {{2025}},
}