https://github.com/cran/bayestestR
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Tip revision: 6313ce21ea98857cf95d996de7978cfd52175e59 authored by Dominique Makowski on 08 April 2021, 04:40 UTC
version 0.9.0
Tip revision: 6313ce2
indicesExistenceComparison.Rmd
---
title: "In-Depth 2: Comparison of Indices of Effect Existence and Significance"
output:
  rmarkdown::html_vignette:
    toc: false
    toc_depth: 3
    fig_width: 10.08
    fig_height: 6  
tags: [r, bayesian, posterior, test]
vignette: >
  \usepackage[utf8]{inputenc}
  %\VignetteIndexEntry{In-Depth 2: Comparison of Indices of Effect Existence}
  %\VignetteEngine{knitr::rmarkdown}
editor_options: 
  chunk_output_type: console
bibliography: bibliography.bib
csl: apa.csl
---

```{r message=FALSE, warning=FALSE, include=FALSE}
library(knitr)
options(knitr.kable.NA = '')
knitr::opts_chunk$set(comment=">", dpi=75, out.width = "100%")
options(digits=2)
```


This vignette can be referred to by citing the following:

- 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
- Makowski, D., Ben-Shachar, M. S., Chen, S. H. A., \& Lüdecke, D. (2019). *Indices of Effect Existence and Significance in the Bayesian Framework*. Frontiers in Psychology 2019;10:2767. [10.3389/fpsyg.2019.02767](https://doi.org/10.3389/fpsyg.2019.02767)

---

# Indices of Effect *Existence* and *Significance* in the Bayesian Framework

A comparison of different Bayesian indices (*pd*, *BFs*, ROPE etc.) is accessible [**here**](https://doi.org/10.3389/fpsyg.2019.02767).

But, in case you don't wish to read the full article, the following table
summarizes the key takeaways!

```{r, echo=FALSE}
knitr::include_graphics("https://www.frontiersin.org/files/Articles/498833/fpsyg-10-02767-HTML/image_m/fpsyg-10-02767-t003.jpg")
```

# Suggestions

If you have any advice, opinion or such, we encourage you to let us know by
opening an [discussion thread](https://github.com/easystats/bayestestR/issues)
or making a pull request.
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