pencal: Penalized Regression Calibration (PRC) for the Dynamic Prediction of Survival (original) (raw)
Computes penalized regression calibration (PRC), a statistical method for the dynamic prediction of survival when many longitudinal predictors are available. PRC is described in Signorelli (2024) <doi:10.48550/arXiv.2309.15600> and in Signorelli et al. (2021) <doi:10.1002/sim.9178>.
Version: | 2.2.2 |
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Depends: | R (≥ 4.1.0) |
Imports: | doParallel, dplyr, foreach, glmnet, lcmm, magic, MASS, Matrix, methods, nlme, purrr, riskRegression, stats, survcomp, survival, survivalROC |
Suggests: | knitr, ptmixed, rmarkdown, survminer |
Published: | 2024-06-12 |
DOI: | 10.32614/CRAN.package.pencal |
Author: | Mirko Signorelli [aut, cre, cph], Pietro Spitali [ctb], Roula Tsonaka [ctb], Barbara Vreede [ctb] |
Maintainer: | Mirko Signorelli <msignorelli.rpackages at gmail.com> |
License: | GPL (≥ 3) |
URL: | https://mirkosignorelli.github.io/r |
NeedsCompilation: | no |
Citation: | pencal citation info |
Materials: | NEWS |
CRAN checks: | pencal results |
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