transportr
Transporting Intervention Effects from One Population to Another
Doubly-robust, non-parametric estimators for the transported average treatment effect from Rudolph, Williams, Stuart, and Diaz (2023) <doi:10.48550/arXiv.2304.00117> and the intent-to-treatment average treatment effect from Rudolph and van der Laan (2017) <doi:10.1111/rssb.12213>. Estimators are fit using cross-fitting and nuisance parameters are estimated using the Super Learner algorithm.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | transportr_0.1.0.tar.gz |
159.9 KiB |
0.1.0 |
rolling linux/noble R-4.5 | transportr_0.1.0.tar.gz |
159.7 KiB |
0.1.0 |
rolling source/ R- | transportr_0.1.0.tar.gz |
14.6 KiB |
0.1.0 |
latest linux/jammy R-4.5 | transportr_0.1.0.tar.gz |
159.9 KiB |
0.1.0 |
latest linux/noble R-4.5 | transportr_0.1.0.tar.gz |
159.7 KiB |
0.1.0 |
latest source/ R- | transportr_0.1.0.tar.gz |
14.6 KiB |
0.1.0 |
2026-04-26 source/ R- | transportr_0.1.0.tar.gz |
14.6 KiB |
0.1.0 |
2026-04-23 source/ R- | transportr_0.1.0.tar.gz |
14.6 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | transportr_0.1.0.zip |
158.0 KiB |
0.1.0 |
2025-04-20 source/ R- | transportr_0.1.0.tar.gz |
14.6 KiB |