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Description

Expected Value of Information.

Methods to calculate the expected value of information from a decision-analytic model. This includes the expected value of perfect information (EVPI), partial perfect information (EVPPI) and sample information (EVSI), and the expected net benefit of sampling (ENBS). A range of alternative computational methods are provided under the same user interface. See Jackson et al. (2022) <doi:10.1146/annurev-statistics-040120-010730>.

voi: a generic package to calculate the expected value of information

Comparison with other packages

voi is pure "command-based" R, with no web interface like 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.

EVPPI computation

  • voi includes all the EVPPI computation methods that are in SAVI (GAM and Gaussian process regression), and includes the INLA method from BCEA.

  • Some other nonparametric regression methods ("earth", "bart") are included in voi, which may improve efficiency for multiparameter EVPPI computation problems with large numbers of parameters.

EVSI computation

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

install.packages("voi")

Development version

remotes::install_github("chjackson/voi")

User guide

voi for Value of Information calculation: package overview

Source code

Github repository.

R-CMD-check test-coverage DOI

Metadata

Version

1.0.2

License

Unknown

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