Bayesian Statistics in Psychological Research

Abstract

One of the key developments in psychological data analysis is the Bayesian implementation. This article aims to introduce Bayesian statistics application in psychological research. A data set of Marital Satisfaction and Positive Affect (n = 200) became an example to compare the regression results based on frequentist and Bayesian statistics. The data analysis examined the influence of positive affect on marital satisfaction. Based upon the prior information and observed data, results suggest that the average of the distribution of the posterior coefficient of positive affect is .31, with a deviation standard of .01 and a credible interval ranging from .30 to .33. The study’s results present the unique approach in interpreting the Bayesian result. This article also outlines diagnostic steps to obtain a robust Bayesian result and avoid misuse of Bayesian statistics. Finally, discussions cover the probability principle in Bayesian analysis and how to interpret its result to encourage Indonesian psychological scientists to implement Bayesian as an alternative to data analysis.