rstpm2: Generalized Survival Models

R implementation of generalized survival models, where g(S(t|x))=eta(t,x) for a link function g, survival S at time t with covariates x and a linear predictor eta(t,x). The main assumption is that the time effect(s) are smooth. For fully parametric models with natural splines, 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 for time. We have also extended the model to include any smooth penalized smoothers from the 'mgcv' package, using penalized likelihood. These models include left truncation, right censoring, interval censoring, gamma frailties and normal random effects. This also includes a smooth implementation of accelerated failure time models.

Version: 1.4.2
Depends: R (≥ 3.0.2), methods, survival, splines
Imports: graphics, Rcpp (≥ 0.10.2), numDeriv, stats, mgcv, bbmle (≥ 1.0.20), fastGHQuad
LinkingTo: Rcpp, RcppArmadillo
Suggests: RUnit, eha
Published: 2018-05-29
Author: Mark Clements [aut, cre], Xing-Rong Liu [aut], Paul Lambert [ctb]
Maintainer: Mark Clements <mark.clements at>
License: GPL-2 | GPL-3
NeedsCompilation: yes
Materials: README NEWS
In views: Survival
CRAN checks: rstpm2 results


Reference manual: rstpm2.pdf
Vignettes: Introduction to the rstpm2 Package
Introduction to the predictnl function
Package source: rstpm2_1.4.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: rstpm2_1.4.2.tgz, r-oldrel: rstpm2_1.4.2.tgz
Old sources: rstpm2 archive

Reverse dependencies:

Reverse suggests: rsimsum, simsurv


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