As demands for computational reproducibility in science are increasing, tools for literate programming are becoming ever more relevant. R Markdown offers a framework to generate reproducible research in various output formats. I present a new package (reproducr) that allows users without any prior knowledge of R Markdown to implement reproducible research practices in their scientific workflows. The reproducr package provides an integrated Rmd-file solution that is fully optimized for two different output formats, HTML and PDF. While in the stage of explorative data analysis and when focusing on content only, researchers may rely on the 'draft mode' of the package that knits to HTML and allows them to interactively explore their data. When in the stage of research dissemination and when focusing on the presentation of results, in contrast, researchers may rely on the 'manuscript mode' that knits to PDF and allows them to circulate a publication-ready version of their working paper or submit it (blinded) for review.
Julia Schulte-Cloos is a Marie Skłodowska-Curie funded LMU Research Fellow at the Geschwister Scholl Institute of Political Science at LMU Munich. Her main research interests lie in comparative politics, political behavior, research methodology, and reproducibility. As an advocate of open science, she is a member of the LMU Open Science Center and part of the catalyst network of the Berkeley Initiative for Transparency in the Social Sciences (BITSS).
You can find the slides of the workshop here: https://reproducr-mzes.netlify.app.