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Ullrika Sahlin. Foto.

Ullrika Sahlin

Universitetslektor

Ullrika Sahlin. Foto.

A robust Bayesian bias-adjusted random effects model for consideration of uncertainty about bias terms in evidence synthesis

Författare

  • Ivette Raices Cruz
  • Matthias C.M. Troffaes
  • Johan Lindström
  • Ullrika Sahlin

Summary, in English

Meta-analysis is a statistical method used in evidence synthesis for combining, analyzing and summarizing studies that have the same target endpoint and aims to derive a pooled quantitative estimate using fixed and random effects models or network models. Differences among included studies depend on variations in target populations (ie, heterogeneity) and variations in study quality due to study design and execution (ie, bias). The risk of bias is usually assessed qualitatively using critical appraisal, and quantitative bias analysis can be used to evaluate the influence of bias on the quantity of interest. We propose a way to consider ignorance or ambiguity in how to quantify bias terms in a bias analysis by characterizing bias with imprecision (as bounds on probability) and use robust Bayesian analysis to estimate the overall effect. Robust Bayesian analysis is here seen as Bayesian updating performed over a set of coherent probability distributions, where the set emerges from a set of bias terms. We show how the set of bias terms can be specified based on judgments on the relative magnitude of biases (ie, low, unclear, and high risk of bias) in one or several domains of the Cochrane's risk of bias table. For illustration, we apply a robust Bayesian bias-adjusted random effects model to an already published meta-analysis on the effect of Rituximab for rheumatoid arthritis from the Cochrane Database of Systematic Reviews.

Avdelning/ar

  • Centrum för miljö- och klimatvetenskap (CEC)
  • Biologiska institutionen
  • eSSENCE: The e-Science Collaboration
  • MERGE: ModElling the Regional and Global Earth system
  • Matematisk statistik
  • Beräkningsvetenskap för hälsa och miljö

Publiceringsår

2022-07-30

Språk

Engelska

Sidor

3365-3379

Publikation/Tidskrift/Serie

Statistics in Medicine

Volym

41

Issue

17

Dokumenttyp

Artikel i tidskrift

Förlag

John Wiley & Sons Inc.

Ämne

  • Probability Theory and Statistics

Nyckelord

  • imprecise probability
  • meta-analysis
  • risk of bias
  • robust Bayesian analysis

Aktiv

Published

Forskningsgrupp

  • Computational Science for Health and Environment

ISBN/ISSN/Övrigt

  • ISSN: 0277-6715