{ "_id": "6a1f089eb401979e7341c16e", "Package": "voi", "Title": "Expected Value of Information", "Version": "1.0.3", "Date": "2024-02-17", "Authors@R": "c(person(given = \"Christopher\", family = \"Jackson\",role = c(\"aut\", \"cre\"),email = \"chris.jackson@mrc-bsu.cam.ac.uk\"),\nperson(given = \"Anna\", family = \"Heath\", role = c(\"aut\"), email = \"anna.heath@sickkids.ca\"),\nperson(given = \"Gianluca\", family = \"Baio\", role = c(\"ctb\"), email = \"g.baio@ucl.ac.uk\", comment=\"Author of code taken from the BCEA package\"),\nperson(given = \"Mark\", family = \"Strong\", role = c(\"ctb\"), email = \"mark.strong@sheffield.ac.uk\", comment=\"Author of code taken from the SAVI package\"),\nperson(given=\"Kofi Placid\", family=\"Adragni\", role=\"ctb\", comment=\"Author of code taken from the ldr package\"),\nperson(given=\"Andrew\", family=\"Raim\", role=\"ctb\",comment=\"Author of code taken from the ldr package\")\n)", "Description": "Methods to calculate the expected value of information\nfrom a decision-analytic model. This includes the expected\nvalue of perfect information (EVPI), partial perfect\ninformation (EVPPI) and sample information (EVSI), and the\nexpected net benefit of sampling (ENBS). A range of\nalternative computational methods are provided under the same\nuser interface. See Heath et al. (2024)\n, Jackson et al. (2022)\n.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.2", "Roxygen": "list(markdown = TRUE)", "URL": "https://chjackson.github.io/voi/", "BugReports": "https://github.com/chjackson/voi/issues", "Additional_repositories": "https://inla.r-inla-download.org/R/stable/", "Repository": "https://chjackson.r-universe.dev", "Date/Publication": "2024-09-09 09:41:58 UTC", "RemoteUrl": "https://github.com/chjackson/voi", "RemoteRef": "HEAD", "RemoteSha": "b43b89593b2c8c8e5e8024a236a77f9a0dda85ed", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-18 06:24:21 UTC", "User": "root" }, "Author": "Christopher Jackson [aut, cre],\nAnna Heath [aut],\nGianluca Baio [ctb] (Author of code taken from the BCEA package),\nMark Strong [ctb] (Author of code taken from the SAVI package),\nKofi Placid Adragni [ctb] (Author of code taken from the ldr package),\nAndrew Raim [ctb] (Author of code taken from the ldr package)", "Maintainer": "Christopher Jackson ", "MD5sum": "3fcc63490172b8941f022dc34b60bf3e", "_user": "chjackson", "_type": "src", "_file": "voi_1.0.3.tar.gz", "_fileid": "7e0bf0e063421479215cd47fa94788db87ba18ac4bab075a989738adcf77f81f", "_filesize": 4759928, "_sha256": "7e0bf0e063421479215cd47fa94788db87ba18ac4bab075a989738adcf77f81f", "_created": "2026-05-18T06:24:21.000Z", "_published": "2026-06-02T16:45:18.784Z", "_distro": "noble", "_jobs": [ { "job": 79123708265, "time": 268, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7050898115" }, { "job": 79123708114, "time": 268, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7050898792" }, { "job": 79123708147, "time": 240, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "ERROR", "artifact": "7050892074" }, { "job": 79123708590, "time": 219, "config": "macos-release-arm64", "r": "4.6.0", "check": "ERROR", "artifact": "7050887329" }, { "job": 79123707086, "time": 280, "config": "source", "r": 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"chjackson", "mastodon": "@cjackstats@fosstodon.org", "description": "Statistician and software developer", "uuid": 7807096 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "mgcv", "role": "Imports" }, { "package": "earth", "role": "Imports" }, { "package": "mvtnorm", "role": "Imports" }, { "package": "progress", "role": "Imports" }, { "package": "dbarts", "role": "Imports" }, { "package": "posterior", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "gridExtra", "role": "Imports" }, { "package": "Matrix", "role": "Imports" }, { "package": "testthat", "role": "Suggests" }, { "package": "BCEA", "role": "Suggests" }, { "package": "INLA", "role": "Suggests" }, { "package": "splancs", "role": "Suggests" }, { "package": "sf", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "rjags", "role": "Suggests" }, { "package": 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EVPPI estimates", "topics": [ "plot.evppi" ] }, { "page": "pop_voi", "title": "Population expected value of information", "topics": [ "pop_voi" ] } ], "_readme": "https://github.com/chjackson/voi/raw/HEAD/README.md", "_rundeps": [ "abind", "backports", "checkmate", "cli", "cpp11", "crayon", "dbarts", "distributional", "earth", "farver", "Formula", "generics", "ggplot2", "glue", "gridExtra", "gtable", "hms", "isoband", "labeling", "lattice", "lifecycle", "magrittr", "Matrix", "matrixStats", "mgcv", "mvtnorm", "nlme", "numDeriv", "pillar", "pkgconfig", "plotmo", "plotrix", "posterior", "prettyunits", "progress", "R6", "RColorBrewer", "rlang", "S7", "scales", "tensorA", "tibble", "utf8", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "plots.Rmd", "filename": "plots.html", "title": "Plots of Value of Information measures", "author": "Christopher Jackson", "engine": "knitr::rmarkdown", "headings": [ "Example EVSI dataset", "EVSI curves", "Expected net benefit of sampling", "Optimal sample size", "Smooth interpolation", "Note about uncertainty", "Curve of optimal sample size", "Probability of a cost-effective trial" ], "created": "2023-04-12 17:39:37", "modified": "2023-04-13 09:38:10", "commits": 4 }, { "source": "voi.Rmd", "filename": "voi.html", "title": "voi for Value of Information calculation: package overview", "author": "Christopher Jackson", "engine": "knitr::rmarkdown", "headings": [ "Simple example model", "Specifying model inputs", "Specifying model outputs", "Expected value of perfect information", "Computation using random sampling", "Using the voi package to calculate EVPI", "Analytic computation", "Expected value of partial perfect information", "Invoking the evppi function.", "Changing the default calculation method", "Gaussian process regression", "Multivariate adaptive regression splines", "INLA method", "Bayesian additive regression trees (BART)", "Tuning the generalized additive model method", "Single-parameter methods", "Traditional 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