{ "_id": "6a1688c9acfb0bcc41d7613d", "Package": "jointVIP", "Title": "Prioritize Variables with Joint Variable Importance Plot in\nObservational Study Design", "Version": "1.0.0", "Authors@R": "c(person(given = \"Lauren D.\",\nfamily = \"Liao\",\nrole = c(\"aut\", \"cre\"),\nemail = \"ldliao@berkeley.edu\",\ncomment = c(ORCID = \"0000-0003-4697-6909\")),\nperson(given = \"Samuel D.\",\nfamily = \"Pimentel\",\nrole = c(\"aut\"),\nemail = \"spi@berkeley.edu\",\ncomment = c(ORCID = \"0000-0002-0409-6586\")))", "Description": "In the observational study design stage,\nmatching/weighting methods are conducted. However, when many\nbackground variables are present, the decision as to which\nvariables to prioritize for matching/weighting is not trivial.\nThus, the joint treatment-outcome variable importance plots are\ncreated to guide variable selection. The joint variable\nimportance plots enhance variable comparisons via unadjusted\nbias curves derived under the omitted variable bias framework.\nThe plots translate variable importance into recommended values\nfor tuning parameters in existing methods. Post-matching and/or\nweighting plots can also be used to visualize and assess the\nquality of the observational study design. The method\nmotivation and derivation is presented in \"Prioritizing\nVariables for Observational Study Design using the Joint\nVariable Importance Plot\" by Liao et al. (2024)\n. See the package paper by\nLiao and Pimentel (2023) for a beginner\nfriendly user introduction.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.1", "Config/testthat/edition": "3", "Collate": "'data.R' 'support.R' 'check_measures.R' 'create_jointVIP.R'\n'create_post_jointVIP.R' 'get_measures.R' 'get_post_measures.R'\n'get_boot_measures.R' 'plot.R' 'print.R' 'summary.R'", "VignetteBuilder": "knitr", "URL": "https://github.com/ldliao/jointVIP,\nhttps://ldliao.github.io/jointVIP/", "BugReports": "https://github.com/ldliao/jointVIP/issues", "LazyData": "true", "Repository": "https://ldliao.r-universe.dev", "Date/Publication": "2025-02-01 00:04:58 UTC", "RemoteUrl": "https://github.com/ldliao/jointvip", "RemoteRef": "HEAD", "RemoteSha": "8d55fdfb3128d604ed4d4207aca8f1a60a3922a0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-27 05:58:24 UTC", "User": "root" }, "Author": "Lauren D. Liao [aut, cre] (ORCID:\n),\nSamuel D. Pimentel [aut] (ORCID:\n)", "Maintainer": "Lauren D. 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Liao", "email": "ldliao@berkeley.edu", "login": "ldliao", "description": "Biostatistician. \n", "uuid": 22989630, "orcid": "0000-0003-4697-6909" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.3", "role": "Depends" }, { "package": "ggrepel", "version": ">= 0.9.2", "role": "Imports" }, { "package": "ggplot2", "version": ">= 3.4.0", "role": "Imports" }, { "package": "causaldata", "role": "Suggests" }, { "package": "devtools", "version": ">= 2.4.5", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "MatchIt", "role": "Suggests" }, { "package": "WeightIt", "role": "Suggests" }, { "package": "optmatch", "role": "Suggests" }, { "package": "optweight", "version": ">= 0.2.4", "role": "Suggests" }, { "package": "rmarkdown", "version": ">= 2.18", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "stringr", "role": "Suggests" } ], "_owner": "ldliao", "_selfowned": true, "_usedby": 0, 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jointVIP object", "topics": [ "bootstrap.plot" ] }, { "page": "brfss", "title": "2015 Behavioral Risk Factor Surveillance System", "topics": [ "brfss" ] }, { "page": "ceiling_dec", "title": "support function for ceiling function with decimals", "topics": [ "ceiling_dec" ] }, { "page": "check_measures", "title": "Check measures Check to see if there is any missing values or variables without any variation or identical rows (only unique rows will be used)", "topics": [ "check_measures" ] }, { "page": "create_jointVIP", "title": "create jointVIP object", "topics": [ "create_jointVIP" ] }, { "page": "create_post_jointVIP", "title": "create post_jointVIP object", "topics": [ "create_post_jointVIP" ] }, { "page": "floor_dec", "title": "support function for floor function with decimals", "topics": [ "floor_dec" ] }, { "page": "get_boot_measures", "title": "Calculate bootstrapped variation additional tool to help calculate the uncertainty of each variable's bias", "topics": [ "get_boot_measures" ] }, { "page": "get_measures", "title": "Prepare data frame to plot standardized omitted variable bias Marginal standardized mean differences and outcome correlation", "topics": [ "get_measures" ] }, { "page": "get_post_measures", "title": "Post-measures data frame to plot post-standardized omitted variable bias", "topics": [ "get_post_measures" ] }, { "page": "one_hot", "title": "support function for one-hot encoding", "topics": [ "one_hot" ] }, { "page": "plot.jointVIP", "title": "plot the jointVIP object", "topics": [ "plot.jointVIP" ] }, { "page": "plot.post_jointVIP", "title": "plot the post_jointVIP object this plot uses the same custom options as the jointVIP object", "topics": [ "plot.post_jointVIP" ] }, { "page": "print.jointVIP", "title": "Obtains a print for jointVIP object", "topics": [ "print.jointVIP" ] }, { "page": "print.post_jointVIP", "title": "Obtains a print for post_jointVIP object", "topics": [ "print.post_jointVIP" ] }, { "page": 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