| Name : R-rstpm2
| |
| Version : 1.5.5
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp154.1.16
| Date : 2024-09-12 11:02:01
|
| Group : Development/Libraries/Other
| Source RPM : R-rstpm2-1.5.5-lp154.1.16.src.rpm
|
| Size : 3.68 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Smooth Survival Models, Including Generalized Survival Models
|
Description :
R implementation of generalized survival models (GSMs), smooth
accelerated failure time (AFT) models and Markov multi-state models.
For the GSMs, 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
< doi:10.1177/0962280216664760>. 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 < doi:10.1002/sim.7451>, and copulas. For the smooth AFTs,
S(t|x) = S_0(t*eta(t,x)), where the baseline survival function
S_0(t)=exp(-exp(eta_0(t))) is modelled for natural splines for eta_0,
and the time-dependent cumulative acceleration factor eta(t,x)=\\int_0^t
exp(eta_1(u,x)) du for log acceleration factor eta_1(u,x). The Markov
multi-state models allow for a range of models with smooth transitions
to predict transition probabilities, length of stay, utilities and
costs, with differences, ratios and standardisation.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.4/x86_64 |
