3. Become a Bayesian master

• Mixed Models
  • Priors
• What’s next?

This vignette can be referred to by citing the package:

• Makowski, D., Ben-Shachar, M. S., & Lüdecke, D. (2019). bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. Journal of Open Source Software, 4(40), 1541. https://doi.org/10.21105/joss.01541

Mixed Models

TO BE CONTINUED.

Priors

TO BE CONTINUED.

What’s next?

The journey to become a true Bayesian master is not over. It is merely the beginning. It is now time to leave the bayestestR universe and apply the Bayesian framework in a variety of other statistical contexts:

• Marginal means
• Contrast analysis
• Testing Contrasts from Bayesian Models with ‘emmeans’ and ‘bayestestR’