Contains a suite of functions for survival analysis in health economics.
These can be used to run survival models under a frequentist (based on maximum likelihood)
or a Bayesian approach (both based on Integrated Nested Laplace Approximation or Hamiltonian
Monte Carlo). To run the Bayesian models, the user needs to install additional modules
(packages), i.e. 'survHEinla' and 'survHEhmc'. These can be installed using
'remotes::install_github' from their GitHub repositories:
(<https://github.com/giabaio/survHEhmc> and <https://github.com/giabaio/survHEinla/>
respectively). 'survHEinla' is based on the package INLA, which is available for download at
<https://inla.r-inla-download.org/R/stable/>. The user can specify a set of parametric models
using a common notation and select the preferred mode of inference. The results can also be
post-processed to produce probabilistic sensitivity analysis and can be used to export the
output to an Excel file (e.g. for a Markov model, as often done by modellers and
practitioners). <doi:10.18637/jss.v095.i14>.
Version: |
2.0.2 |
Depends: |
methods, R (≥ 3.6.0), flexsurv, dplyr, ggplot2 |
Imports: |
rms, xlsx, tools, tibble, tidyr |
Suggests: |
survHEinla, survHEhmc, INLA, rstan, testthat (≥ 3.0.0) |
Published: |
2024-10-04 |
DOI: |
10.32614/CRAN.package.survHE |
Author: |
Gianluca Baio [aut, cre],
Andrea Berardi [ctb],
Philip Cooney [ctb],
Andrew Jones [ctb],
Nathan Green [ctb] |
Maintainer: |
Gianluca Baio <g.baio at ucl.ac.uk> |
BugReports: |
https://github.com/giabaio/survHE/issues |
License: |
GPL (≥ 3) |
URL: |
https://github.com/giabaio/survHE,
https://gianluca.statistica.it/software/survhe/ |
NeedsCompilation: |
yes |
SystemRequirements: |
GNU make |
Additional_repositories: |
https://inla.r-inla-download.org/R/stable/,
https://giabaio.github.io/drat/ |
Materials: |
README NEWS |
CRAN checks: |
survHE results |