Modern Bayesian Statistics in Clinical Research pp 111-118 | Cite as

# Bayesian Pearson Correlation Analysis

## Abstract

In studies with two continuous variables usually named the x-values and y-values a linear relation between the two variables can be assessed with the help of the Pearson correlation coefficient R. R is a measure of strength of association, and varies from −1 to +1. Instead of a traditional Pearson correlation analysis a Bayesian analysis of linear correlation is possible.

A traditional analysis of Pearson linear correlation analysis provided an r-value of 0.483 with an F statistic of 10047, p-value 0.003. A Bayesian Analysis of Pearson linear correlation provided support in favor of the traditional test with a Bayes factor of 0.105.

This was less wide than the 95% confidence interval of the traditional Pearson linear correlation which was

Thus, the Bayesian analysis provided slightly better statistics than did the traditional Pearson correlation analysis.

## Suggested Reading^{1}^{,}^{2}

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- SPSS for starters and 2nd levelers 2nd edition, 2015Google Scholar
- Clinical data analysis on a pocket calculator 2nd edition, 2016Google Scholar
- Understanding clinical data analysis from published research, 2016Google Scholar
- Modern Meta-analysis, 2017Google Scholar
- Regression Analysis in Clinical Research, 2018Google Scholar