ccwr
Clone-Censor-Weight Methods for Target Trial Emulation
Provides methods for clone-censor-weight analyses that emulate target trials with grace-period treatment strategies using observational time-to-event data. Tools clone participants across strategies, apply strategy-specific artificial censoring, and estimate inverse probability of censoring weights using pooled logistic or Cox models, fit weighted outcome models, and obtain subject-level bootstrap confidence intervals by repeating the complete analysis. The methods are described by Maringe et al. (2020) <doi:10.1093/ije/dyaa057> and Gaber et al. (2024) <doi:10.1002/cam4.70461>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.2 |
rolling linux/jammy R-4.5 | ccwr_0.0.2.tar.gz |
161.6 KiB |
0.0.2 |
rolling linux/noble R-4.5 | ccwr_0.0.2.tar.gz |
161.7 KiB |
0.0.2 |
rolling source/ R- | ccwr_0.0.2.tar.gz |
118.1 KiB |
0.0.2 |
latest linux/jammy R-4.5 | ccwr_0.0.2.tar.gz |
161.6 KiB |
0.0.2 |
latest linux/noble R-4.5 | ccwr_0.0.2.tar.gz |
161.7 KiB |
0.0.2 |
latest source/ R- | ccwr_0.0.2.tar.gz |
118.1 KiB |
0.0.2 |
2026-04-23 source/ R- | ccwr_0.0.2.tar.gz |
0 B |