shinybrms

Description

The R package shinybrms provides a graphical user interface (GUI) for fitting Bayesian regression models using the R package brms which in turn relies on Stan. The shinybrms GUI is a Shiny app.

To get an impression of the shinybrms app, have a look at this page. The following text explains how to launch the shinybrms app.

Launching the shinybrms app

There are two options for launching the shinybrms app:

• Install the R package shinybrms (either from CRAN or from GitHub) and then launch the shinybrms app from the installed package.
• Launch the shinybrms app directly from GitHub.

The first option is described in the following section “With installation of shinybrms”. The second option is described in the subsequent section “Without installation of shinybrms”. In both cases, you need to perform the following steps first:

1. Install R (see the R homepage).
2. Install the R package rstan (see the “RStan Getting Started” GitHub page for instructions; make sure to use install.packages("rstan", [...], dependencies = TRUE) with [...] as advised on the “RStan Getting Started” GitHub page).

With installation of shinybrms

1. Install the R package shinybrms either from CRAN or from GitHub. The GitHub version might be more recent than the CRAN version. You also need to decide whether you want to use the example datasets from the R packages lme4, MASS, and rstanarm or not.

   • If you don’t want to use the example datasets from the R packages lme4, MASS, and rstanarm, then the R code for installing shinybrms from CRAN and GitHub (respectively) is as follows:

     • To install shinybrms from CRAN:

       install.packages("shinybrms")

     • To install shinybrms from GitHub:

       if(!requireNamespace("devtools", quietly = TRUE)){
         install.packages("devtools")
       }
       devtools::install_github("fweber144/shinybrms")

   • If you want to use the example datasets from the R packages lme4, MASS, and rstanarm, then the R code for installing shinybrms from CRAN and GitHub (respectively) is as follows:

     • To install shinybrms from CRAN:

       install.packages("shinybrms", dependencies = TRUE)

     • To install shinybrms from GitHub:

       if(!requireNamespace("devtools", quietly = TRUE)){
         install.packages("devtools")
       }
       devtools::install_github("fweber144/shinybrms", dependencies = TRUE)

2. Launch the shinybrms app by either running the following R code:

   library(shinybrms)
   launch_shinybrms()

   or this R code which ensures that the app opens up in the default web browser (helpful e.g. if you are using RStudio):

   library(shinybrms)
   launch_shinybrms(launch.browser = TRUE)

Without installation of shinybrms

1. Install the R package brms. You may use the following R code for this:

   install.packages("brms")

2. If you want to use the example datasets from the R packages lme4, MASS, and rstanarm, you need to install these packages. You may use the following R code for this:

   install.packages(c("lme4", "MASS", "rstanarm"))

3. Launch the shinybrms app directly from GitHub by either running the following R code:

   shiny::runGitHub("fweber144/shinybrms",
                    subdir = "inst/shinybrms_app")

   or this R code which ensures that the app opens up in the default web browser (helpful e.g. if you are using RStudio):

   shiny::runGitHub("fweber144/shinybrms",
                    subdir = "inst/shinybrms_app",
                    launch.browser = TRUE)