MissMecha
A Python package for missing data mechanism simulation and analysis.
MissMecha is an open-source Python package designed for researchers and practitioners to simulate, visualize, and evaluate missing data mechanisms, including MCAR, MAR, and MNAR.
With MissMecha, you can generate controlled missing patterns, evaluate imputation methods, and explore the impact of different missing data types on your downstream models. It provides a unified API for simulation, imputation, and evaluation — making it a complete toolkit for incomplete data research.
Why MissMecha?
MissMecha addresses the gap in reproducible missing data research by offering:
- Simulation of MCAR, MAR, MNAR mechanisms.
- Flexible control over missing rate and structure.
- Visual analysis and statistical summaries.
- Imputation performance evaluation utilities.
- Reproducible experimental setup.
MissMecha is available on PyPI and fully documented on https://echoid.github.io/MissMecha/.
Ready to empower your missing data research?
Get started on GitHub.