This vignette can be referred to by citing the package:

citation("see")
#> 
#>   Lüdecke et al., (2021). see: An R Package for Visualizing Statistical
#>   Models. Journal of Open Source Software, 6(64), 3393.
#>   https://doi.org/10.21105/joss.03393
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Article{,
#>     title = {{see}: An {R} Package for Visualizing Statistical Models},
#>     author = {Daniel Lüdecke and Indrajeet Patil and Mattan S. Ben-Shachar and Brenton M. Wiernik and Philip Waggoner and Dominique Makowski},
#>     journal = {Journal of Open Source Software},
#>     year = {2021},
#>     volume = {6},
#>     number = {64},
#>     pages = {3393},
#>     doi = {10.21105/joss.03393},
#>   }

Introduction

modelbased is a package in easystats ecosystem to help with model-based estimations, to easily compute of marginal means, contrast analysis and model predictions.

For more, see: https://easystats.github.io/modelbased/

Setup and Model Fitting

library(modelbased)
library(rstanarm)
library(ggplot2)
library(see)

theme_set(theme_modern())

model <- stan_glm(Sepal.Width ~ Species, data = iris, refresh = 0)

Pairwise Contrasts

contrasts <- estimate_contrasts(model)
means <- estimate_means(model)

plot(contrasts, means)