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  3. A Tutorial On Bayesian Hypothesis Testing Of Correlation Coefficients Using The Bfpack-module In Jasp.
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  3. A Tutorial On Bayesian Hypothesis Testing Of Correlation Coefficients Using The Bfpack-module In Jasp.

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A tutorial on Bayesian hypothesis testing of correlation coefficients using the BFpack-module in JASP.

Joris Mulder1, Julius Pfadt2, Eric-Jan Wagenmakers2

  • 1Department of Methodology and Statistics, Tilburg University, Warandelaan 2, 5037 AB, Tilburg, the Netherlands. j.mulder3@tilburguniversity.edu.

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View abstract on PubMed

Summary
This summary is machine-generated.

This tutorial introduces Bayesian hypothesis testing for correlation coefficients using JASP's BFpack module. It offers a flexible alternative to classical p-values for analyzing associations between variables.

Keywords:
Bayes factorsCorrelations coefficientsHypothesis testingPosterior probabilities

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Area of Science:

  • Statistics
  • Psychometrics
  • Quantitative Psychology

Background:

  • Correlation coefficients are crucial for quantifying linear associations between variables in scientific research.
  • Classical hypothesis testing using p-values for correlations has known limitations and limited software support for alternatives.
  • Limited availability of statistical software hinders the adoption of Bayesian testing procedures for correlation coefficients.

Purpose of the Study:

  • To demonstrate how to conduct Bayesian hypothesis tests on various correlation coefficients using the BFpack module in JASP.
  • To provide researchers with a user-friendly, open-source tool for advanced correlation analysis, overcoming limitations of classical methods.

Main Methods:

  • Utilized the BFpack module within the JASP software for performing Bayesian hypothesis tests.
  • Showcased testing for product-moment, polyserial, and tetrachoric correlations, including partial correlations.
  • Demonstrated Bayesian testing of zero correlations and comparisons between dependent and independent correlations.

    • Main Results:

    • The BFpack module in JASP enables flexible Bayesian hypothesis testing for diverse correlation types.
    • The tutorial successfully illustrates the application of Bayesian methods as an alternative to classical p-value approaches.
    • The study highlights the accessibility of advanced Bayesian correlation testing through free, open-source software.

    Conclusions:

    • The BFpack module in JASP offers a powerful and accessible solution for Bayesian hypothesis testing of correlation coefficients.
    • This approach provides researchers with a robust alternative to classical methods, mitigating known limitations.
    • The tutorial facilitates wider adoption of Bayesian statistical methods in correlation analysis across research disciplines.