2014PubMedRequires access

[Bayesian statistics: what, how and why?].

Willem H. Woertman, Hans Groenewoud, Gert Jan van der Wilt

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Abstract

Bayesian statistics is an alternative form of statistics that provides a way to systematically integrate new information with existing information. Bayesian methods are very suitable for evidence synthesis. Bayesian outcomes are easier to interpret than standard statistical outcomes. For instance, Bayesian methods allow for determining the probability that a difference in effect between two treatments will be clinically relevant. The use of Bayesian methods is becoming more prevalent.

About this research paper

What this paper is about

Bayesian statistics is an alternative form of statistics that provides a way to systematically integrate new information with existing information. Bayesian methods are very suitable for evidence synthesis. Bayesian outcomes are easier to interpret than standard statistical outcomes. For instance, Bayesian methods allow for determining the probability that a difference in effect between two treatments will be clinically relevant. The use of Bayesian methods is becoming more prevalent.

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Available abstract

Bayesian statistics is an alternative form of statistics that provides a way to systematically integrate new information with existing information. Bayesian methods are very suitable for evidence synthesis. Bayesian outcomes are easier to interpret than standard statistical outcomes. For instance, Bayesian methods allow for determining the probability that a difference in effect between two treatments will be clinically relevant. The use of Bayesian methods is becoming more prevalent.

Key concepts: Bayesian probability, Bayesian statistics, Bayesian average, Bayesian experimental design, Statistics, Medicine, Bayesian hierarchical modeling, Bayesian inference

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