In DominiqueMakowski/bayestestR: Understand and Describe Bayesian Models and Posterior Distributions

library(knitr)
knitr::opts_chunk$set(
  echo = TRUE,
  collapse = TRUE,
  warning = FALSE,
  message = FALSE,
  comment = "#>",
  eval = TRUE
)

All package vignettes are available at https://easystats.github.io/bayestestR/.

Function Overview

• Function Reference

Get Started

• Get Started with Bayesian Analysis

Examples

1. Initiation to Bayesian models
2. Confirmation of Bayesian skills
3. Become a Bayesian master

Articles

• Credible Intervals (CI))
• Region of Practical Equivalence (ROPE)
• Probability of Direction (pd)
• Bayes Factors

In-Depths

• Comparison of Point-Estimates
• Indices of Effect Existence and Significance in the Bayesian Framework
• Mediation Analysis using Bayesian Regression Models

Guidelines

• Reporting Guidelines

DominiqueMakowski/bayestestR documentation built on April 25, 2024, 8:20 a.m.