Online Stats Training
Published November 4, 2020 | Version v1
Lesson Open

Tutorial: jamovi for Bayesian analyses with default priors

Authors/Creators

  • 1. Utrecht University

Description

This tutorial explains how to conduct Bayesian analyses in jamovi (The jamovi project, 2020) with default priors for starters. With step-by-step illustrations, we perform and interpret core results of correlation analysis, multiple linear regression, t-test, and one-way analysis of variance, all from a Bayesian perspective. To enhance readers’ understanding, a brief comparison between the Bayesian and frequentist approach is provided in each analytic option. After the tutorial, we expect readers can perform basic Bayesian analyses and distinguish its approach from the frequentist approach.

If readers need fundamentals of jamovi and ways to interpret results from a frequentist statistics viewpoint, we recommend following jamovi for beginners. The current tutorial presumes that readers are familiar with conducting and interpreting frequentist statistical analyses in jamovi.

Notes

Since we continuously improve the tutorials, let us know via Github (https://github.com/Rensvandeschoot/Tutorials) if you discover mistakes, or if you have additional resources we can refer to.

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Additional details

Related works

References
Dataset: 10.5281/zenodo.3962123 (DOI)
Lesson: 10.5281/zenodo.4008373 (DOI)
Lesson: 10.5281/zenodo.4117884 (DOI)

References

  • Kass, R. E., & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90(430), 773-795.
  • Kruschke, J. (2014). Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (2nd ed.). Academic Press.
  • The jamovi project. (2020). jamovi (Version 1.2.27)[Computer software].
  • Van de Schoot, R. (2020). Popularity Dataset for Online Stats Training [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3962123
  • Van de Schoot, R., & Depaoli, S. (2014). Bayesian analyses: Where to start and what to report. The European Health Psychologist, 16(2), 75-84.
  • Van de Schoot, R., Kaplan, D., Denissen, J., Asendorpf, J. B., Neyer, F. J., & Van Aken, M. A. (2014). A gentle introduction to Bayesian analysis: Applications to developmental research. Child development, 85(3), 842-860. https://doi.org/10.1111/cdev.12169
  • Van de Schoot, R., Van der Velden, F., Boom, J., & Brugman, D. (2010). Can at-risk young adolescents be popular and anti-social? Sociometric status groups, anti-social behaviour, gender and ethnic background. Journal of adolescence, 33(5), 583-592. https://doi.org/10.1016/j.adolescence.2009.12.004