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nbpInference

Inference on Average Treatment Effects for Continuous Treatments

Conduct inference on the sample average treatment effect for a matched (observational) dataset with a continuous treatment. Equipped with calipered non-bipartite matching, bias-corrected sample average treatment effect estimation, and covariate-adjusted variance estimation. Matching, estimation, and inference methods are described in Frazier, Heng and Zhou (2024) <doi:10.48550/arXiv.2409.11701>.

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VersionRepositoryFileSize
1.0.3 rolling linux/jammy R-4.5 nbpInference_1.0.3.tar.gz 53.1 KiB
1.0.3 rolling linux/noble R-4.5 nbpInference_1.0.3.tar.gz 53.1 KiB
1.0.3 rolling source/ R- nbpInference_1.0.3.tar.gz 33.2 KiB
1.0.3 latest linux/jammy R-4.5 nbpInference_1.0.3.tar.gz 53.1 KiB
1.0.3 latest linux/noble R-4.5 nbpInference_1.0.3.tar.gz 53.1 KiB
1.0.3 latest source/ R- nbpInference_1.0.3.tar.gz 33.2 KiB
1.0.3 2026-04-26 source/ R- nbpInference_1.0.3.tar.gz 33.2 KiB
1.0.3 2026-04-23 source/ R- nbpInference_1.0.3.tar.gz 33.2 KiB
1.0.3 2026-04-09 windows/windows R-4.5 nbpInference_1.0.3.zip 56.4 KiB

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