Abstract
In studies with one sample continuous data a single outcome per patient is usually compared to zero.
Instead of t-test also a Bayesian one sample normal test is possible. A one sample t-test of a hypertension study provided a result significantly different from zero at t = 2.429, p = 0.038. A Bayesian one sample t-test provided support in favor of the above t-test with a Bayes factor of 0.506. The 95% confidence intervals of (1) the traditional test, (2) the Bayesian test, and (3) the bootstrap t-test were respectively
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0.1165–3.2835
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−0.1769 to 3.5769
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0.4000–2.9000.
Therefore, some overfitting cannot be ruled out. We conclude that in this chapter the Bayes factor is a better test statistic than the traditional p-value is.
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Notes
- 1.
To readers requesting more background, theoretical and mathematical information of computations given, several textbooks complementary to the current production and written by the same authors are available.
- 2.
All of them have been written by the same authors, and have been edited by Springer Heidelberg Germany.
Suggested Reading ,
To readers requesting more background, theoretical and mathematical information of computations given, several textbooks complementary to the current production and written by the same authors are available.
All of them have been written by the same authors, and have been edited by Springer Heidelberg Germany.
Statistics applied to clinical studies 5th edition, 2012
Machine learning in medicine a complete overview, 2015
SPSS for starters and 2nd levelers 2nd edition, 2015
Clinical data analysis on a pocket calculator 2nd edition, 2016
Understanding clinical data analysis from published research, 2016
Regression Analysis in Clinical Research, 2018
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Cleophas, T.J., Zwinderman, A.H. (2018). Bayesian Tests for One Sample Continuous Data. In: Modern Bayesian Statistics in Clinical Research . Springer, Cham. https://doi.org/10.1007/978-3-319-92747-3_3
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DOI: https://doi.org/10.1007/978-3-319-92747-3_3
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