SMARTbayesR
Bayesian Set of Best Dynamic Treatment Regimes and Sample Size in SMARTs for Binary Outcomes
Permits determination of a set of optimal dynamic treatment regimes and sample size for a SMART design in the Bayesian setting with binary outcomes. Please see Artman (2020) <arXiv:2008.02341>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.0 |
rolling linux/jammy R-4.5 | SMARTbayesR_2.0.0.tar.gz |
98.7 KiB |
2.0.0 |
rolling linux/noble R-4.5 | SMARTbayesR_2.0.0.tar.gz |
98.6 KiB |
2.0.0 |
rolling source/ R- | SMARTbayesR_2.0.0.tar.gz |
22.7 KiB |
2.0.0 |
latest linux/jammy R-4.5 | SMARTbayesR_2.0.0.tar.gz |
98.7 KiB |
2.0.0 |
latest linux/noble R-4.5 | SMARTbayesR_2.0.0.tar.gz |
98.6 KiB |
2.0.0 |
latest source/ R- | SMARTbayesR_2.0.0.tar.gz |
22.7 KiB |
2.0.0 |
2026-04-26 source/ R- | SMARTbayesR_2.0.0.tar.gz |
22.7 KiB |
2.0.0 |
2026-04-23 source/ R- | SMARTbayesR_2.0.0.tar.gz |
22.7 KiB |
2.0.0 |
2026-04-09 windows/windows R-4.5 | SMARTbayesR_2.0.0.zip |
101.8 KiB |
2.0.0 |
2025-04-20 source/ R- | SMARTbayesR_2.0.0.tar.gz |
22.7 KiB |