survHE

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.

Last 30 days

This package has been downloaded 743 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 30 times.

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Last 365 days

This package has been downloaded 7,349 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Jul 21, 2024 with 81 downloads.

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