Bayesian analysis


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Bayesian analysis

A decision analysis which permits the calculation of the probability that one treatment is superior to another based on the observed data and prior beliefs. In Bayesian analysis, subjectivity is not a liability, but rather explicitly allows different opinions to be formally expressed and evaluated.

Bayesian analysis

A decision-making analysis that '…permits the calculation of the probability that one treatment is superior based on the observed data and prior beliefs…subjectivity of beliefs is not a liability, but rather explicitly allows different opinions to be formally expressed and evaluated.' See Algorithm, Critical pathway, Decision analysis.

Bayes the·o·rem

(bāyz thē'ŏr-ĕm)
A method of calculating statistical probability that combines a prior estimate of probability with statistics derived from subsequent events or experiments. Although it lacks mathematical rigor, it is often used to infer degree of risk in various medical settings.
Synonym(s): bayesian analysis.
References in periodicals archive ?
The bottom line is that it is highly unlikely that our finding from our Bayesian analysis that Democracy Prep has a positive impact on voter registration and turnout is the result of chance.
Bayesian Analysis of the Association between Family-Level Factors and Siblings' Dental Caries.
Bayesian analysis of longitudinal data using growth curve models.
Bayesian analysis of twinning and ovulation rates using a multiple-trait threshold model and Gibbs sampling.
In this section we present the results of the Bayesian analysis for the time series for monthly averages of natural streamflows, measured in the period 1931 to 2010, in Furnas hydroelectric dam, assuming joint modeling for the mean and variance autoregressive gamma models, that is, we assume that the observations of the interest are generated from a conditional gamma density function given by f ([y.sub.t] |[H.sub.t-1]), where [H.sub.t-1]) is the information up to time t - 1 and [Y.sub.t] has conditional mean and conditional variance given respectively by [[micro].sub.t] = E([Y.sub.t] | [H.sub.t-1]) and [mathematical expression not reproducible], and defined by (10) and (11).
We have considered a Bayesian analysis of binary data in testing hypotheses of equivalence.
Considering as null hypothesis that mapping of the crude rate does not clearly identify the formation of agglomerates of deaths, and that the Empirical Bayesian analysis provides a re-configuration of the distribution of mortality and formation of agglomerates, the aim of this study was to compare the results obtained between the estimate by the crude rate and the Bayesian method for the rate of deaths from oral and oropharynx cancer, in the State of Minas Gerais, in 2012.
In this article, we propose a framework for incorporating uncertainty into the length-based estimator of mortality that is based on von Bertalanffy growth function (VBGF) parameters determined with Bayesian analysis and asymmetric error distributions.
In Bayesian analysis, one could impose an informative prior to reflect the trend that cannot be inferred from the data.
The (co) variance components and genetic parameters were estimated using the linear mixed and threshold animal models, one-character Bayesian analysis, and applications for the linear (GIBBS1F90) and threshold (THRGIBBS1F90) models (MISZTAL et al., 2002).
Phylogenetic trees were reconstructed with MrBayes v3.2.1 [18] using Bayesian analysis coupled with Markov Chain Monte Carlo methods of phylogenetic inference.