rstpm2: Generalized Survival Models
R implementation of generalized survival models, where g(S(t(x))) for a link function g, survival S at time t with covariates x is modelled using a linear predictor. The main assumption is that the time effect(s) are smooth. For fully parametric models, this re-implements Stata's 'stpm2' function, which are flexible parametric survival models developed by Royston and colleagues. We have extended the parametric models to include any smooth parametric smoothers. We have also extended the model to include any smooth penalized smoothers from the 'mgcv' package, using penalized likelihood. These models have all been extended to include left truncation, right censoring, interval censoring, frailties and normal random effects.
| Version: |
1.3.1 |
| Depends: |
R (≥ 2.10), methods, survival, splines |
| Imports: |
graphics, Rcpp (≥ 0.10.2), numDeriv, stats, mgcv, bbmle (≥
1.0.3), fastGHQuad |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
RUnit, gaussquad |
| Published: |
2016-02-24 |
| Author: |
Mark Clements [aut, cre], Xing-Rong Liu [aut], Paul Lambert [ctb] |
| Maintainer: |
Mark Clements <mark.clements at ki.se> |
| BugReports: |
http://github.com/mclements/rstpm2/issues |
| License: |
GPL-2 | GPL-3 |
| URL: |
http://github.com/mclements/rstpm2 |
| NeedsCompilation: |
yes |
| Materials: |
README |
| CRAN checks: |
rstpm2 results |
Downloads: