I don’t know if The Stan Forums are the right place for this announcement, but I thought it might not harm:
This package provides a GUI (a Shiny app) for fitting Bayesian regression models using
brms. Of course, most of you don’t need a GUI for fitting Bayesian regression models. But
shinybrms was developed to spread Bayesian regression models out to a broader public which is not familiar with R. Perhaps some of you are giving advise in Bayesian regression modeling to people from this broader public and want to give those people the opportunity to fit their models themselves. That’s where
shinybrms comes in. Since it relies on Shiny,
shinybrms may be run on a server and then accessed via a web browser (so that users don’t even need to install R and the necessary R packages).
The current version is 1.0.1 and offers only limited features:
- For the (univariate) outcome: only a Gaussian, Bernoulli, or negative binomial distribution.
- For the predictors: Only non-varying (a.k.a. population-level or “fixed”) effects are supported. Varying (a.k.a. group-level or “random”) effects are not supported yet. Interactions are supported, though.
- Most of
brms's special features, like monotonic effects for ordinal predictors, non-linear effects, or the possibility to specify standard errors for the outcome (for meta-analyses and meta-regressions) are not supported yet.
- For the inspection of the output, only a short summary (from
brms::summary.brmsfit()) and the possibility to launch
Of course, the missing features are on my to-do list. Additionally, I plan to include (for example):
- a custom output inspection directly in
shinybrms(additionally to the possibility to launch
- model selection possibilities.
Further suggestions for improvements are very welcome.
Note that the current version has not been tested yet with R 4.0.0 (as
shinybrms v1.0.1 has been released on CRAN on March 26, 2020, i.e. before the final release of R 4.0.0). This is the first thing on my to-do list.