heemod - Health Economic Evaluation MODelling
heemod is an R toolset for health economic evaluation modelling. It aims to provide a simple and consistent interface for Markov models specification and comparison (for decision trees or cohort simulation). Non-homogeneous Markov models (with time varying properties) are supported.
Most of the analyses presented in Decision Modelling for Health Economic Evaluation can be performed with heemod. See vignette("i-reproduction", "heemod") for an exact reproduction of the analyses from the book.
You can install:
- the latest released version from CRAN with:
install.packages("heemod")- the latest development version from github with:
devtools::install_github("pierucci/heemod@devel")Main features
- Graphical user interface with
shiny. - Time-varying transition probabilities.
- Time-varying values attached to states.
- Microsimulation-like models.
- Probabilistic uncertainty analysis.
- Deterministic sensitivity analysis.
- Multiple state membership correction methods (life-table, half-cycle, etc.).
- Demographic analysis to compute population-level results.
- Heterogeneity analysis.
- Parallel computing support.
Learning heemod
To get started read the introduction in vignette("a-introduction", "heemod"). Time-varying probabilities and values are explained in vignette("b-time-dependency", "heemod").
Specific analysis examples (mostly inspired from Decision Modelling for Health Economic Evaluation) can be found in the following vignettes:
- Homogeneous Markov model in
vignette("c-homogeneous", "heemod"). - Non-homogeneous Markov model in
vignette("d-non-homogeneous", "heemod"). - Probabilistic uncertainty analysis in
vignette("e-probabilistic", "heemod"). - Deterministic sensitivity analysis in
vignette("f-sensitivity", "heemod"). - Heterogeneity & Demographic analysis in
vignette("g-heterogeneity", "heemod"). - Running the models from tabular inputs in
vignette("h-tabular", "heemod").
Devs
Kevin Zarca and Antoine Filipović-Pierucci.