dame-flame is a Python package for performing matching for observational causal inference on datasets containing discrete covariates. It implements the Dynamic Almost Matching Exactly (DAME) and Fast, Large-Scale Almost Matching Exactly (FLAME) algorithms, which match treatment and control units on subsets of the covariates. The resulting matched groups are interpretable, because the matches are made on covariates, and high-quality, because machine learning is used to determine which covariates are important to match on.
Please reach out to let our team know if you’re using this, or if you have any questions. You are welcome to contact Neha Gupta at firstname.lastname@example.org. We also check public comments or questions posted on GitHub.