chestR
Kernel-Weighted Cox Regression for Treatment Effect Heterogeneity
Explores treatment effect heterogeneity and candidate predictive biomarkers by re-fitting weighted Cox proportional hazards models on a biomarker grid. Kernel weights centred at each grid point produce local coefficient estimates that can be visualised across biomarker space. Builds on ideas related to graphical Cox treatment-covariate interaction methods [see Bonetti and Gelber (2004) <doi:10.1093/biostatistics/kxh002> and local partial-likelihood approaches Fan, Lin and Zhou (2006) <doi:10.1214/009053605000000796>].
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | chestR_0.1.0.tar.gz |
101.4 KiB |
0.1.0 |
rolling linux/noble R-4.5 | chestR_0.1.0.tar.gz |
101.3 KiB |
0.1.0 |
rolling source/ R- | chestR_0.1.0.tar.gz |
66.1 KiB |
0.1.0 |
latest linux/jammy R-4.5 | chestR_0.1.0.tar.gz |
101.4 KiB |
0.1.0 |
latest linux/noble R-4.5 | chestR_0.1.0.tar.gz |
101.3 KiB |
0.1.0 |
latest source/ R- | chestR_0.1.0.tar.gz |
66.1 KiB |
0.1.0 |
2026-04-23 source/ R- | chestR_0.1.0.tar.gz |
0 B |