THREE BAYESIAN TEST INDEXES FOR NORMAL DISTRIBUTIONS
- 1 Tokyo University of Science, Japan
Abstract
In clinical trials, data that are consistent with a normal distribution are often regarded as candidates for primary evaluation variables. In such cases, t-tests are frequently used to compare different groups of data. However, the repeated use of t-tests leads to problems with multiplicity. This study proposes three new indexes that are based on (Kawasaki and Miyaoka, 2012; 2013). These indexes can be used to evaluate the superiority, non-inferiority and equivalency of population means for normal distributions. These new indexes are constructed based on the Bayesian framework and can be used to prevent multiplicity issues. We apply these three new indexes to actual data in order to demonstrate their usefulness.
DOI: https://doi.org/10.3844/jmssp.2014.244.246
Copyright: © 2014 Yohei Kawasaki. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Bayesian Inference
- Normal Distribution
- Non-Inferiority
- Equivalency
- Superiority