A Bayesian framework to account for uncertainty due to missing binary outcome data in pairwise meta‐analysis
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Summary
This framework allows one to make the best use of evidence produced from RCTs with missing outcome data in a meta‐analysis, accounts for any uncertainty induced by missing data and fits easily into a wider evidence synthesis framework for medical decision making.
- Type
- article
- Published
- 2015-03-24
- Cited by
- 33
- References
- 49
- Access
- Open access
- OpenAlex
- https://openalex.org/W1777048973
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:14633245
Keywords
Missing data, Outcome (game theory), Pairwise comparison, Computer science, Bayesian probability
References
- Estimation and adjustment of bias in randomized evidence by using mixed treatment comparison meta‐analysis
- Statistical Analysis With Missing Data (2nd ed.) (Book)
- Evidence Synthesis for Decision Making in Healthcare
- Bayesian measures of model complexity and fit
- NICE DSU Technical Support Document 2: A Generalised Linear Modelling Framework for Pairwise and Network Meta-Analysis of Randomised Controlled Trials
- WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility
- Strategy for Modelling Nonrandom Missing Data Mechanisms in Observational Studies Using Bayesian Methods
- The direct use of likelihood for significance testing
- Experiences in elicitation
- Cochrane Handbook for Systematic Reviews of Interventions
- Influence of Reported Study Design Characteristics on Intervention Effect Estimates From Randomized, Controlled Trials
- Simultaneous comparison of multiple treatments: combining direct and indirect evidence
- Analysis of Longitudinal Trials with Protocol Deviation: A Framework for Relevant, Accessible Assumptions, and Inference via Multiple Imputation
- Multiparameter evidence synthesis in epidemiology and medical decision‐making: current approaches
- Pattern-Mixture Models for Multivariate Incomplete Data
- Eliciting and using expert opinions about dropout bias in randomized controlled trials
- A practical introduction to multivariate meta-analysis
- Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis by DANIELS, M. J. and HOGAN, J. W
- Simple approaches to assess the possible impact of missing outcome information on estimates of risk ratios, odds ratios, and risk differences.
- Bias modelling in evidence synthesis
Cited by
- Handling trial participants with missing outcome data when conducting a meta-analysis: a systematic survey of proposed approaches
- GRADE guidelines 17: assessing the risk of bias associated with missing participant outcome data in a body of evidence.
- Missing binary data extraction challenges from Cochrane reviews in mental health and Campbell reviews with implications for empirical research
- Systematic reviews do not adequately report or address missing outcome data in their analyses: a methodological survey.
- A systematic survey shows that reporting and handling of missing outcome data in networks of interventions is poor
- Modeling missing binary outcome data while preserving transitivity assumption yielded more credible network meta-analysis results.
- Potentially missing data are considerably more frequent than definitely missing data: a methodological survey of 638 randomized controlled trials.
- U.S. Corporate Energy Productivity, Greenhouse Gas Productivity, and Return on Equity
- Dealing with missing outcome data in meta‐analysis
- Participants' outcomes gone missing within a network of interventions: Bayesian modeling strategies
- An empirical comparison of Bayesian modelling strategies for missing binary outcome data in network meta-analysis
- A guidance was developed to identify participants with missing outcome data in randomized controlled trials.
- Helicobacter pylori eradication treatment for gastric carcinoma prevention in asymptomatic or dyspeptic adults: systematic review and Bayesian meta-analysis of randomised controlled trials
- Interventions to prevent spontaneous preterm birth in high-risk women with singleton pregnancy: a systematic review and network meta-analysis
- GRADE-Leitlinien: 17. Beurteilung des Bias-Risikos durch fehlende Endpunkt-Daten im Evidenzkörper
- Pharmacologic and non-pharmacologic interventions to prevent hypersensitivity reactions of non-ionic iodinated contrast media: a systematic review protocol
- Comparison of exclusion, imputation and modelling of missing binary outcome data in frequentist network meta-analysis
- Effectiveness and adverse events of topical and allergen immunotherapy for atopic dermatitis: a systematic review and network meta-analysis protocol
- Pattern-mixture model in network meta-analysis of binary missing outcome data: one-stage or two-stage approach?
- Continuous(ly) missing outcome data in network meta-analysis: A one-stage pattern-mixture model approach
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