I’m working on the next update of my sjPlot-package, which will get a generic
plot_model() method, which plots any kind of regression model, with different plot types being supported (forest plots for estimates, marginal effects and predictions, including displaying interaction terms, …).
The package also supports
rstanarm models. Since these are typically presented in a slightly different way (e.g., „outer“ and „inner“ probability of credible intervals), I implemented a special handling for these models, for which I wanted to show a quick preview here:
m <- stan_glm(
mpg ~ cyl + disp + drat + wt + gear + am,
data = mtcars
plot_model(m) + theme_sjplot()
The thin error bars represent the High Density Intervals (HDI) specified in the
ci.lvl argument, the thick bar is the 50%-HDI, and the white point is the posterior median.
This is still work in progress, the latest version is on GitHub…
Tagged: data visualization, ggplot, R, rstan, rstanarm, rstats, sjPlot