Bayesian Replication of Mortality and Morbidity Risk Effects in Chronic Disease Research - Cristian Antony Ramos Vera (Universidad de las Ciencias Médicas de Cienfuegos, 2021)
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.