---
title: "3. Become a Bayesian master"
output: 
  rmarkdown::html_vignette:
    toc: true
    fig_width: 10.08
    fig_height: 6
tags: [r, bayesian, posterior, test]
vignette: >
  \usepackage[utf8]{inputenc}
  %\VignetteIndexEntry{Example 3: Become a Bayesian master}
  %\VignetteEngine{knitr::rmarkdown}
editor_options: 
  chunk_output_type: console
bibliography: bibliography.bib
csl: apa.csl
---

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

---

```{r message=FALSE, warning=FALSE, include=FALSE}
library(knitr)
options(knitr.kable.NA = '')
knitr::opts_chunk$set(
  comment = ">",
  message = FALSE,
  warning = FALSE,
  out.width = "100%"
)

options(digits=2)

set.seed(333)
```

```{r echo=FALSE, fig.cap="Yoda Bayes (896 BBY - 4 ABY).", fig.align='center', out.width="80%"}
knitr::include_graphics("https://github.com/easystats/easystats/raw/master/man/figures/bayestestR/YodaBayes.jpg")
```

## Mixed Models

TO BE CONTINUED.

### Priors

TO BE CONTINUED.


## What's next?

The journey to become a true Bayesian master is not yet 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**](https://easystats.github.io/modelbased/articles/estimate_means.html)
- [**Contrast analysis**](https://easystats.github.io/modelbased/articles/estimate_contrasts.html)
- [**Testing Contrasts from Bayesian Models with 'emmeans' and 'bayestestR'**](https://easystats.github.io/blog/posts/bayestestr_emmeans/)