christophergandrud/drlearner
Doubly Robust Machine Learner with sample splitting for Heterogeneous Treatment Effect Estimation and Approximately Optimal Treatments using Best Linear Projections
When you need to decide if an individual should receive a specific treatment or intervention, but the effect depends on their unique characteristics, this tool helps you identify who benefits most. It takes observational data (individual characteristics, whether they received treatment, and the outcome) and outputs an estimated individual-level treatment effect. This is ideal for researchers, policy makers, or strategists who want to optimize targeting for treatments like marketing campaigns, medical interventions, or educational programs.
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Use this if you need to estimate how a treatment affects different individuals based on their traits, especially with large datasets where other methods might be too slow or memory-intensive.
Not ideal if you're looking for a simple average treatment effect across an entire population or if computational speed is not a primary concern for smaller datasets.
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R
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Last pushed
Jan 09, 2023
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