DISCOURSE

I introduce the DISCOURSE framework – Data-simulation via Iterative Stochastic Combinatorial Optimization Using Reported Summary Estimates. The primary scope of the algorithmic framework is to reconstruct complete datasets using only summary statistics, giving researchers a way - when raw data are unavailable - to conduct follow-up analyses and inform replication study decision‑making.

Usage

The method is available as R package and comprehensive ShinyApp.

Web App

You can use the app at https://sebastian-lortz.shinyapps.io/discourse/. Expect longer computation time compared to running the app locally.

Installation

You can install the latest version of the R package discourse like so:

# install devtools if needed
if (!requireNamespace("devtools")) {install.packages("devtools")}

# install from GitHub
devtools::install_github("sebastian-lortz/discourse")

Run

You can launch the ShinyApp locally by running:

discourse::run_app()

Citation

Please cite discourse if you use it. To cite the software, use:

Lortz SAJ (2025). discourse: Data-simulation via Iterative Stochastic Combinatorial Optimization Using Reported Summary Estimates. R package version 0.0.1.000, https://sebastian-lortz.github.io/discourse/, https://github.com/sebastian-lortz/discourse.

Or copy the reference information to your BibTeX file:

@Manual{discourse,
  title        = {discourse: Data‐simulation via Iterative Stochastic Combinatorial Optimization Using Reported Summary Estimates},
  author       = {S. A. J. Lortz},
  year         = {2025},
  note         = {R package version 0.0.1.000},
  url          = {https://github.com/sebastian-lortz/discourse}
}

Code of Conduct

I am open to feedback and new ideas. Please mind the Contributor Code of Conduct.

About

You are reading the doc about version: 0.0.1.000

This README has been compiled on 2025-06-27 14:10:12.