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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
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 |
Dependencies (latest)
Imports
Suggests
- testthat (>= 3.0.0)