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 Heath et al. (2024) <doi:10.1201/9781003156109>, Jackson et al. (2022) <doi:10.1146/annurev-statistics-040120-010730>.
Version: 1.0.3 Depends: R (≥ 3.5.0) Imports: mgcv, earth, mvtnorm, progress, dbarts, posterior, ggplot2, gridExtra, Matrix Suggests: testthat, BCEA, INLA, splancs, sf, knitr, rmarkdown, rjags, truncnorm, scales, dplyr, heemod Published: 2024-09-16 DOI: 10.32614/CRAN.package.voi Author: Christopher Jackson [aut, cre], Anna Heath [aut], Gianluca Baio [ctb] (Author of code taken from the BCEA package), Mark Strong [ctb] (Author of code taken from the SAVI package), Kofi Placid Adragni [ctb] (Author of code taken from the ldr package), Andrew Raim [ctb] (Author of code taken from the ldr package) Maintainer: Christopher Jackson <chris.jackson at mrc-bsu.cam.ac.uk> BugReports: https://github.com/chjackson/voi/issues License: GPL-3 URL: https://chjackson.github.io/voi/ NeedsCompilation: no Additional_repositories: https://inla.r-inla-download.org/R/stable/ Materials: README NEWS CRAN checks: voi resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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