Lege Artis Medicinae

[The medical application of Bayesian T-tests and traditional parametric T-tests]

MOLNÁR D. László1

APRIL 20, 2016

Lege Artis Medicinae - 2016;26(04)

[Bayesian statistical learning is a mixture of the hypothetico-deductive (“top down”) and inductive (“bottom up”) perspective of data analysis with a combination of prior distributions and the data using the Bayes theorem. The resulting posterior distributions are, in a figurative sense, similar to the middle part of a sand-clock. By analogy the upper part of this clock represents the hypothetico-deductive part in terms of prior distributions, while the lower part of that represents the inductive part in terms of the data. The prior distributions will then be continuously replaced with the posterior distributions in a learning cycle. The “top-down” and the “bottom up” methods are simultaneously used both in medicine and management sciences. On the other hand, traditional frequentist statistics can primarily be considered as an inductive method, which is mainly based on the data collected. Comparison of a scale variable measured in two groups is shown with the traditional parametric t-tests, nonparametric permutation test and various Bayesian t-tests. The corresponding R and WinBUGS codes are presented. ]

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  1. Szociomed Kft.

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