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Type 2 Tobit Sample Selection Models with Bayesian Additive Regression Trees

arXiv — stat.ML•Tuesday, November 4, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
A new study introduces Type 2 Tobit Bayesian Additive Regression Trees (TOBART-2), which enhances the accuracy of individual-specific treatment effect estimates. This advancement is significant because it addresses the common issue of biased estimates caused by sample selection, offering a more robust method that incorporates nonlinearities and model uncertainty. By utilizing sums of trees in both selection and outcome equations, this model could lead to more reliable data analysis in various fields, making it a noteworthy contribution to statistical methodologies.
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