An introduction to a Bayesian method for meta-analysis: The confidence profile method.
The Confidence Profile Method is a new Bayesian method that can be used to assess technologies where the available evidence involves a variety of experimental designs, types of outcomes, and effect measures; a variety of biases; combinations of biases and nested bases; uncertainty about biases; an underlying variability in the parameter of interest; indirect evidence; and technology families. The result of an analysis with the Confidence Profile Method is a posterior distribution for the parameter of interest, posterior distributions for other parameters, and a covariance matrix for all the parameters in the model. The posterior distributions incorporate all the uncertainty the assessor chooses to describe about any of the parameters used in the analysis.
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Related Subject Headings
- Selection Bias
- Research Design
- Randomized Controlled Trials as Topic
- Probability
- Models, Statistical
- Methods
- Meta-Analysis as Topic
- Likelihood Functions
- Humans
- Health Policy & Services
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Selection Bias
- Research Design
- Randomized Controlled Trials as Topic
- Probability
- Models, Statistical
- Methods
- Meta-Analysis as Topic
- Likelihood Functions
- Humans
- Health Policy & Services