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Bayesian methods rely on the same assumptions as the maximum likelihood methods. In addition, Bayesian methods also assume that appropriate and reasonable distributions have been used for prior estimates for sensitivity and specificity of the tests being evaluated and prevalence in the population(s). For critical distributions where prior knowledge is lacking it may be appropriate to use an uninformative (uniform) prior distribution.