Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research

Bayesian inference allows the replication of clinical findings by means of the Bayes factor which is referred to as the probability of the data under one hypothesis in relation to another. The use of the Bayesian approach is important, as an improved way of drawing statistical conclusions from clini...

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Main Author: Cristian Antony Ramos Vera
Format: Article
Language:Spanish
Published: Universidad de las Ciencias Médicas de Cienfuegos 2021-04-01
Series:Revista Finlay
Subjects:
Online Access:http://www.revfinlay.sld.cu/index.php/finlay/article/view/980
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author Cristian Antony Ramos Vera
author_facet Cristian Antony Ramos Vera
author_sort Cristian Antony Ramos Vera
collection DOAJ
description Bayesian inference allows the replication of clinical findings by means of the Bayes factor which is referred to as the probability of the data under one hypothesis in relation to another. The use of the Bayesian approach is important, as an improved way of drawing statistical conclusions from clinical data that provides greater validity to significant conclusions. This approach allows a correct estimation and interpretation of the confidence intervals given the data as opposed to frequency intervals. It is useful for studies that integrate chronic diseases to report the different effect magnitudes evidence degree, such as the risk association of the most common factors with morbidity and mortality.
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spelling doaj.art-afd37364162e400186068df24731dbb02022-12-22T00:41:16ZspaUniversidad de las Ciencias Médicas de CienfuegosRevista Finlay2221-24342021-04-01112119121501Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease ResearchCristian Antony Ramos Vera0Facultad de Ciencias de la Salud. Universidad César Vallejo. Lima. Perú.Bayesian inference allows the replication of clinical findings by means of the Bayes factor which is referred to as the probability of the data under one hypothesis in relation to another. The use of the Bayesian approach is important, as an improved way of drawing statistical conclusions from clinical data that provides greater validity to significant conclusions. This approach allows a correct estimation and interpretation of the confidence intervals given the data as opposed to frequency intervals. It is useful for studies that integrate chronic diseases to report the different effect magnitudes evidence degree, such as the risk association of the most common factors with morbidity and mortality.http://www.revfinlay.sld.cu/index.php/finlay/article/view/980teorema de bayesfactores de riesgomortalidadmorbilidadenfermedad crónica
spellingShingle Cristian Antony Ramos Vera
Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research
Revista Finlay
teorema de bayes
factores de riesgo
mortalidad
morbilidad
enfermedad crónica
title Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research
title_full Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research
title_fullStr Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research
title_full_unstemmed Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research
title_short Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research
title_sort bayesian replication of mortality and morbidity risk effects in chronic disease research
topic teorema de bayes
factores de riesgo
mortalidad
morbilidad
enfermedad crónica
url http://www.revfinlay.sld.cu/index.php/finlay/article/view/980
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