shinymrp allows users to apply Multilevel Regression and Poststratification (MRP) methods to a variety of datasets, from electronic health records to sample survey data, through an end-to-end Bayesian data analysis workflow. Whether you’re a researcher, analyst, or data engineer, shinymrp provides robust tools for data cleaning, exploratory analysis, flexible model building, and insightful result visualization.
You can use shinymrp in two flexible ways:
The graphical user interface (GUI), built with the Shiny framework, is designed for newcomers and those looking for an interactive, code-free analysis experience.
Launch the app locally in R with:
::run_app() shinymrp
Explore the Shiny app without installation via our online demo.
Need a walk-through? Watch our step-by-step video tutorial.
Leverage the full flexibility of the exported R6 classes for a programmatic workflow, ideal for advanced users and those integrating MRP into larger R projects.
Import shinymrp in scripts or R Markdown documents just like any other R package:
library(shinymrp)
To get started, install the latest development version of
shinymrp from GitHub using
remotes
:
# If 'remotes' is not installed:
install.packages("remotes")
::install_github("mrp-interface/shinymrp") remotes
The package installation does not automatically install all prerequisites. Specifically, shinymrp uses CmdStanR as the bridge to run Stan, a state-of-the-art platform for Bayesian modeling. Stan requires a modern C++ toolchain (compiler and GNU Make build utility).
For detailed guidance, check our introductory vignette: Getting started with shinymrp.
This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.