{ "_id": "6a12e35eacfb0bcc41d23f69", "Package": "gapclosing", "Title": "Estimate Gaps Under an Intervention", "Version": "1.0.3", "Authors@R": "person(given = \"Ian\",\nfamily = \"Lundberg\",\nrole = c(\"aut\", \"cre\"),\nemail = \"ianlundberg@ucla.edu\",\ncomment = c(ORCID = \"https://orcid.org/0000-0002-1909-2270\"))", "Description": "Provides functions to estimate the disparities across\ncategories (e.g. Black and white) that persists if a treatment\nvariable (e.g. college) is equalized. Makes estimates by\ntreatment modeling, outcome modeling, and doubly-robust\naugmented inverse probability weighting estimation, with\nstandard errors calculated by a nonparametric bootstrap.\nCross-fitting is supported. Survey weights are supported for\npoint estimation but not for standard error estimation; those\napplying this package with complex survey samples should\nconsult the data distributor to select an appropriate approach\nfor standard error construction, which may involve calling the\nfunctions repeatedly for many sets of replicate weights\nprovided by the data distributor. The methods in this package\nare described in the accompanying paper:\n.", "License": "MIT + file LICENSE", "URL": "https://ilundberg.github.io/gapclosing/", "BugReports": "https://github.com/ilundberg/gapclosing/issues", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-24 11:35:33 UTC", "User": "root" }, "Author": "Ian Lundberg [aut, cre]\n()", "Maintainer": "Ian Lundberg ", "Config/testthat/edition": "3", "Language": "en-US", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://ilundberg.r-universe.dev", "Date/Publication": "2026-05-22 23:35:14 UTC", "RemoteUrl": "https://github.com/ilundberg/gapclosing", "RemoteRef": "HEAD", "RemoteSha": "db0d20dc26e4fd229c496dcd9aaf4363bc67332e", "MD5sum": "74e7eb918b69a2ec8730ce6d82f4bef1", "_user": "ilundberg", "_type": "src", "_file": "gapclosing_1.0.3.tar.gz", "_fileid": 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"source": "gapclosing.Rmd", "filename": "gapclosing.html", "title": "gapclosing: An R package to estimate gap closing estimands", "engine": "knitr::rmarkdown", "headings": [ "1. Data structure", "2. Quick overview: Functionality", "3. Detailed procedures: Customize your call", "Step 1. Define the intervention", "Step 2. Make causal assumptions for identification", "Step 3. Specify a treatment model and/or an outcome model", "Choose an estimation algorithm", "Why doubly robust? A side note", "Why sample splitting? Another side note", "Produce standard errors", "4. Estimate by machine learning: Two examples", "Estimation with Generalized Additive Models (GAMs) via mgcv", "Estimation with random forests via ranger", "Estimates from these three algorithms are roughly the same", "A warning about complex estimators", "5. Estimate with stochastic assignment rules", "6. 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