dirttee: Distributional Regression for Time to Event Data
Semiparametric distributional regression methods (expectile,
quantile and mode regression) for time-to-event variables with
right-censoring; uses inverse probability of censoring weights or
accelerated failure time models with auxiliary likelihoods. Expectile
regression using inverse probability of censoring weights has been
introduced in Seipp et al. (2021) “Weighted Expectile Regression for
Right-Censored Data” <doi:10.1002/sim.9137>, mode regression for
time-to-event variables has been introduced in Seipp et al. (2022)
“Flexible Semiparametric Mode Regression for Time-to-Event Data”
<doi:10.1177/09622802221122406>.
| Version: |
1.0.2 |
| Depends: |
expectreg (≥ 0.5.0), R (≥ 3.6.0) |
| Imports: |
formula.tools, MASS, Matrix, mgcv, nloptr, provenance, rlang, splines, survival |
| Published: |
2023-12-21 |
| DOI: |
10.32614/CRAN.package.dirttee |
| Author: |
Alexander Seipp [aut, cre], Fabian Otto-Sobotka [aut] |
| Maintainer: |
Alexander Seipp <alexander.seipp at uni-oldenburg.de> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
dirttee results |
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