survHE: Survival Analysis in Health Economic Evaluation

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: (<> and <> respectively). 'survHEinla' is based on the package INLA, which is available for download at <>. 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: 2.0.1
Depends: methods, R (≥ 3.6.0), flexsurv, dplyr, ggplot2
Imports: rms, xlsx, tools, tibble
Suggests: survHEinla, survHEhmc, INLA, rstan, testthat (≥ 3.0.0)
Published: 2023-03-19
Author: Gianluca Baio [aut, cre], Andrea Berardi [ctb], Philip Cooney [ctb], Andrew Jones [ctb], Nathan Green [ctb]
Maintainer: Gianluca Baio <g.baio at>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: NEWS
CRAN checks: survHE results


Reference manual: survHE.pdf


Package source: survHE_2.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): survHE_2.0.1.tgz, r-oldrel (arm64): survHE_2.0.1.tgz, r-release (x86_64): survHE_2.0.1.tgz, r-oldrel (x86_64): survHE_2.0.1.tgz
Old sources: survHE archive


Please use the canonical form to link to this page.