Bayesian methods for clinicians

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BIDHENDI YARANDI RAZIEH; MOHAMMAD KAZEM; ZERAATI HOJJAT; RAMEZANI TEHRANI FAHIMEH; MANSOURNIA MOHAMMAD ALI

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Journal Paper

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Journal: Medical Journal of The Islamic Republic of Iran Year:2020 | Volume:34 | Issue:1 Page(s): 0-0

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Title

Bayesian methods for clinicians

Author(s)

Keywords

Bayesian inference

Prior information

MCMC

Data augmentation

Abstract

Background: The Bayesian methods have received more attention in medical research. It is considered as a natural paradigm for dealing with applied problems in the sciences and also an alternative to the traditional frequentist approach. However, its concept is somewhat difficult to grasp by nonexperts. This study aimed to explain the foundational ideas of the Bayesian methods through an intuitive example in medical science and to illustrate some simple examples of Bayesian data analysis and the interpretation of results delivered by Bayesian analyses. In this study, data sparsity, as a problem which could be solved by this approach, was presented through an applied example. Moreover, a common sense description of Bayesian inference was offered and some illuminating examples were provided for medical investigators and nonexperts. Methods: Data augmentation prior, MCMC, and Bayes factor were introduced. Data from the Khuzestan study, a 2-phase cohort study, were applied for illustration. Also, the effect of vitamin D intervention on pregnancy outcomes was studied. Results: Unbiased estimate was obtained by the introduced methods. Conclusion: Bayesian and Data augmentation as the advanced methods provide sufficient results and deal with most data problems such as sparsity.

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APA: Copy

MOHAMMAD, KAZEM, ZERAATI, HOJJAT, RAMEZANI TEHRANI, FAHIMEH, & MANSOURNIA, MOHAMMAD ALI. (2020). Bayesian methods for clinicians. MEDICAL JOURNAL OF THE ISLAMIC REPUBLIC OF IRAN (MJIRI), 34(1), 0-0. SID. https://sid.ir/paper/749646/en

Vancouver: Copy

MOHAMMAD KAZEM, ZERAATI HOJJAT, RAMEZANI TEHRANI FAHIMEH, MANSOURNIA MOHAMMAD ALI. Bayesian methods for clinicians. MEDICAL JOURNAL OF THE ISLAMIC REPUBLIC OF IRAN (MJIRI)[Internet]. 2020;34(1):0-0. Available from: https://sid.ir/paper/749646/en

IEEE: Copy

KAZEM MOHAMMAD, HOJJAT ZERAATI, FAHIMEH RAMEZANI TEHRANI, and MOHAMMAD ALI MANSOURNIA, “Bayesian methods for clinicians,” MEDICAL JOURNAL OF THE ISLAMIC REPUBLIC OF IRAN (MJIRI), vol. 34, no. 1, pp. 0–0, 2020, [Online]. Available: https://sid.ir/paper/749646/en

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