Welcome to R-miss-tastic

A community-driven platform on missing data in statistics and machine learning.

Project Overview

R-miss-tastic is a platform funded by the R Consortium (Infrastructure Steering Committee). Its mission is to provide a centralized, evolving reference for managing missing data in statistical workflows.

Our goals:

• ✅ Curate a list of existing packages,
• 📚 Share available literature,
• 🧠 Provide theoretical and practical tutorials,
• 🔄 Showcase analysis workflows in both R and Python,
• 👥 Highlight main contributors and actors,
• 📊 List popular datasets.

This website provides the main methods, references and implementations (in R and Python) for managing missing data — whether to impute, estimate or predict.
Click here for the article introducing this project.

If you are a user, you will find the main methods available depending on the nature of your data sets; courses on missing data and pipelines of analyses will help you determine which method is most suitable for your analysis.

If you are a researcher, you will be able to find datasets, simulation tools, and templates to benchmark your methods against existing ones.

Get Involved

Our vision is to:

• 🧩 Federate the community working on missing data,
• ✍️ Encourage contributions from researchers and practitioners.

Maintainers

This website is proudly sponsored by the R Consortium and maintained by:

• Julie Josse
• Aude Sportisse
• Nathalie Vialaneix
• Christophe Muller
• Krystyna Grzesiak

Former maintainers:

• Nicholas Tierney
• Imke Mayer