knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )

brmstools is an R package available on GitHub.

brmstools provides convenient plotting and post-processing functions for brmsfit objects (bayesian regression models fitted with the brms R package).

brmstools is in beta version so will probably break down with some inputs: Suggestions for improvements and bug reports are welcomed. For anything more complex I strongly recommend using brms' native functions instead (particularly its `marginal_effects()`

and `hypothesis()`

methods. Combined with ggplot2 those functions will create any visualization you can think of.)

Install brmstools from GitHub with devtools:

# install.packages("devtools") devtools::install_github("mvuorre/brmstools")

Loading brmstools also loads the brms package:

```
library(brmstools)
```

Notably, `forest()`

draws forest plots for meta-analytic and multilevel models:

load(here::here("vignettes/forest-plots/fit_rem.rda")) forest(fit_rem)

`panels()`

draws panel plots:

load(here::here("vignettes/forest-plots/fit_ml.rda")) panels(fit_ml, xvar = "Days")

`spaghetti()`

draws spaghetti plots:

spaghetti(fit_ml, xvar = "Days")

`coefplot()`

draws coefficient plots:

coefplot(fit_ml)

Examples and instructions can be found at https://mvuorre.github.io/brmstools.

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