https://github.com/chjackson/voi
Methods to calculate the Expected Value of Information
https://github.com/chjackson/voi
Last synced: 7 months ago
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Methods to calculate the Expected Value of Information
- Host: GitHub
- URL: https://github.com/chjackson/voi
- Owner: chjackson
- Created: 2019-12-10T17:44:17.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-09-16T11:39:40.000Z (over 1 year ago)
- Last Synced: 2025-10-22T05:59:44.889Z (7 months ago)
- Language: R
- Homepage: https://chjackson.github.io/voi/
- Size: 58.2 MB
- Stars: 7
- Watchers: 3
- Forks: 6
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
Awesome Lists containing this project
README
# voi: a generic package to calculate the expected value of information
* A common interface for several methods to calculate the
- Expected Value of (Partial) Perfect Information and the
- Expected Value of Sample Information
* A project of the [ConVOI Group: the Collaborative Network for Value of Information](https://www.convoi-group.org/)
## Comparison with other packages
`voi` is pure "command-based" R, with no web interface like [SAVI](https://github.com/Sheffield-Accelerated-VoI/SAVI).
* The R commands in `voi` are clean and consistent: they all have the same basic interface, so you can switch between computational methods easily.
* Outputs are all in "tidy" data frames for consistency, and to facilitate post-processing and plotting with modern tools such as [ggplot2](https://ggplot2.tidyverse.org/).
#### EVPPI computation
* `voi` includes all the [EVPPI computation](https://chjackson.github.io/voi/articles/voi.html#evppi) methods that are in [SAVI](https://github.com/Sheffield-Accelerated-VoI/SAVI) (GAM and Gaussian process regression), and includes the INLA method from [BCEA](https://cran.r-project.org/package=BCEA).
* Some other nonparametric regression methods ([`"earth"`](https://chjackson.github.io/voi/articles/voi.html#earth), [`"bart"`](https://chjackson.github.io/voi/articles/voi.html#bart)) are included in `voi`, which may improve efficiency for multiparameter EVPPI computation problems with large numbers of parameters.
#### EVSI computation
* `voi` is the first package to implement a range of [EVSI computation](https://chjackson.github.io/voi/articles/voi.html#evsi) methods: nonparametric regression, moment matching and importance sampling. A simple model for the [expected net benefit of sampling](https://chjackson.github.io/voi/articles/plots.html) is also included.
#### In summary
* `voi` will not benefit you if you want a web interface, or if you just need single-parameter EVPPI and are happy with SAVI/BCEA.
* `voi` will benefit you if you want to calculate EVSI, or multiparameter EVPPI with large numbers of parameters.
## Installation
Stable version
```{r}
install.packages("voi")
```
Development version
```{r}
remotes::install_github("chjackson/voi")
```
## User guide
[`voi` for Value of Information calculation: package overview](https://chjackson.github.io/voi/articles/voi.html)
## Source code
[Github repository](https://github.com/chjackson/voi)
[](https://github.com/chjackson/voi/actions/workflows/R-CMD-check.yaml)
[](https://github.com/chjackson/voi/actions/workflows/test-coverage.yaml)
[](https://zenodo.org/badge/latestdoi/227181181)