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.
Segen's Medical Dictionary. © 2012 Farlex, Inc. All rights reserved.

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.
McGraw-Hill Concise Dictionary of Modern Medicine. © 2002 by The McGraw-Hill Companies, Inc.

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.
Medical Dictionary for the Health Professions and Nursing © Farlex 2012
References in periodicals archive ?
Our approach is different and novel in a sense that we employed the Bayesian inference for the estimation of the parameters of commonly used growth models for sheep data.
Estimates of genetic parameters via Bayesian Inference were calculated with the aid of GIBBS1F90 and THRGIBBS1F90 applications, used for linear and threshold models, respectively [10] by testing chains with 2 and 4 million cycles.
The Bayesian inference assumes the image is a random field and obtains the solution as the probability distribution of the field.
Resultant uncertainty in the six communitywide metrics of trophic structure (Layman et al., 2007) for the five species of consumers, calculated using Bayesian inference. Black dots represent each mode, and grey boxes the credible intervals for 50%, 75%, and 95%, from dark to light, respectively (Jackson et al., 2011).
The data-mining method using Bayesian inference has the same advantages as conventional data-mining methods and is capable of detecting causal relationships among variables.
Zhang, "Off-grid direction of arrival estimation using sparse Bayesian inference," IEEE Transactions on Signal Processing, vol.
Stern, "Recent theoretical progress on an information geometrodynamical approach to chaos," in Proceedings of The Bayesian Inference And Maximum Entropy Methods in Science And Engineering: Proceedings of The 28Th International Workshop on Bayesian Inference And Maximum Entropy Methods in Science And Engineering, pp.
Missing data are easily handled in Bayesian inference by treating them as another set of parameters.
Bayesian inference is the process or the logic to calculate or revise the probability of belief (hypostasis).
On probability, using the principles of Bayesian inference, he shows the effect of false positives and why having prior knowledge before a diagnosis is important.
Bayesian inference is described in the literature as a suitable method for fault detection and fault classification in condition monitoring systems [7], [8].
The approach will use Bayesian Inference to incorporate a priori knowledge of the design alternatives that support the elicited belief of the decision maker before obtaining any information on the design alternatives.

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