https://github.com/aphp/heemod
Markov Models for Health Economic Evaluations
https://github.com/aphp/heemod
Last synced: about 1 year ago
JSON representation
Markov Models for Health Economic Evaluations
- Host: GitHub
- URL: https://github.com/aphp/heemod
- Owner: aphp
- License: gpl-3.0
- Created: 2022-07-13T12:37:23.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2024-09-11T12:35:53.000Z (almost 2 years ago)
- Last Synced: 2025-03-26T09:21:21.057Z (over 1 year ago)
- Language: R
- Homepage: https://aphp.github.io/heemod/
- Size: 32.4 MB
- Stars: 14
- Watchers: 2
- Forks: 2
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# heemod - Health Economic Evaluation MODelling
Markov Models for Health Economic Evaluations. An implementation of the modelling and reporting features described in reference textbooks and guidelines: deterministic and probabilistic sensitivity analysis, heterogeneity analysis, time dependency on state-time and model-time (semi-Markov and non-homogeneous Markov models), etc.
You can install:
* the latest released version from CRAN with:
```r
install.packages("heemod")
```
* the latest development version from github with:
```r
devtools::install_github("aphp/heemod")
```
* `heemod` can be cited with:
Filipović-Pierucci A, Zarca K and Durand-Zaleski I (2017).
[“Markov Models for Health Economic Evaluation: The R
Package heemod.”](https://arxiv.org/abs/1702.03252) *ArXiv e-prints*. R package version
0.8.0, 1702.03252
## Features
Main features:
* Accounting for time-dependency:
* For both model time and state time.
* Time-varying transition probabilities.
* Time-varying values attached to states.
* Probabilistic uncertainty analysis (PSA).
* With correlated resampling.
* Covariance analysis for PSA.
* Expected value of perfect information (EVPI).
* Deterministic sensitivity analysis (DSA).
Other features:
* Multiple state membership correction methods (life-table, custom method, etc.).
* Demographic analysis to compute population-level results.
* Heterogeneity analysis.
* Parallel computing support.
* Features for budget impact analysis.
* Interface with [SAVI](https://savi.shef.ac.uk/SAVI) and [BCEA](https://gianluca.statistica.it/software/bcea/).
Most of the analyses presented in [Decision Modelling for Health Economic Evaluation](https://global.oup.com/academic/product/decision-modelling-for-health-economic-evaluation-9780198526629) can be performed with `heemod`. See the *Reproducing Exact Results from DMHEE* vignette for an exact reproduction of the analyses from the book.
## Learning heemod
To get started read the *An Introduction to* `heemod` vignette. Specific analysis examples (mostly inspired from [Decision Modelling for Health Economic Evaluation](https://global.oup.com/academic/product/decision-modelling-for-health-economic-evaluation-9780198526629)) can be found in the package vignettes.
## Devs
Kevin Zarca and Antoine Filipović-Pierucci.
## Contributors
* [Matthew Wiener](https://github.com/MattWiener)
* [Zdenek Kabat](https://github.com/zkabat)
* [Vojtech Filipec](https://github.com/vojtech-filipec)
* [Jordan Amdahl](https://github.com/jrdnmdhl)
* [Yonatan Carranza Alarcon](https://github.com/salmuz)
* [Vince Daniels](https://github.com/daniels4321)