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Welcome to the MALTS Python Package Documentation!

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pymalts2 is a Python package for performing matching for observational causal inference on datasets containing continuous, categorical, or mixed covariates. It uses exact matching for discrete variables and learns generalized Mahalanobis distances for continuous variables. Instead of a predetermined distance metric, the covariates contributing more towards predicting the outcome are given higher weights.

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Please reach out to let our team know if you’re using this, or if you have any questions! Contact Harsh Parikh at harsh.parikh@duke.edu.