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.
Eddy
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Center for Health Policy, Duke University, Durham, North Carolina 27706.
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Shachter
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D001499:Bayes Theorem; D006801:Humans; D016013:Likelihood Functions; D015201:Meta-Analysis as Topic; D008722:Methods; D015233:Models, Statistical; D011336:Probability; D016032:Randomized Controlled Trials as Topic / Q000592:standards; D012107:Research Design / Q000592:standards; D015983:Selection Bias