{ "_id": "6a1fea3fb401979e7343e8b6", "Package": "optmatch", "Version": "0.10.8.9003", "Title": "Functions for Optimal Matching", "Description": "Distance based bipartite matching using minimum cost flow,\noriented to matching of treatment and control groups in\nobservational studies ('Hansen' and 'Klopfer' 2006\n). Routines are provided to\ngenerate distances from generalised linear models (propensity\nscore matching), formulas giving variables on which to limit\nmatched distances, stratified or exact matching directives, or\ncalipers, alone or in combination.", "Authors@R": "c(person(\"Ben\", \"Hansen\", role = \"aut\", email = \"ben.hansen@umich.edu\"),\nperson(\"Mark\", \"Fredrickson\", role = \"aut\", email = \"mark.m.fredrickson@gmail.com\"),\nperson(\"Josh\", \"Errickson\", role = c(\"cre\",\"aut\"), email = \"jerrick@umich.edu\"),\nperson(\"Josh\", \"Buckner\", role = \"aut\"),\nperson(\"Adam\", \"Rauh\", role = \"ctb\"))", "LazyData": "true", "License": "MIT + file LICENSE", "License_is_FOSS": "yes", "License_restricts_use": "no", "URL": "http://optmat.ch, https://github.com/markmfredrickson/optmatch", "BugReports": "https://github.com/markmfredrickson/optmatch/issues", "Additional_repositories": "https://errickson.net/rrelaxiv", "Collate": "'DenseMatrix.R' 'InfinitySparseMatrix.R' 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}, { "page": "compare_optmatch", "title": "Compares the equality of optmatch objects, ignoring attributes and group names.", "topics": [ "compare_optmatch" ] }, { "page": "dbind", "title": "Diagonally bind together subgroup-specific distances", "topics": [ "dbind" ] }, { "page": "dimnames-InfinitySparseMatrix", "title": "Get and set dimnames for InfinitySparseMatrix objects", "topics": [ "dimnames,InfinitySparseMatrix-method", "dimnames<-,InfinitySparseMatrix,list-method", "dimnames<-,InfinitySparseMatrix,NULL-method" ] }, { "page": "distUnion", "title": "Combine multiple distance specifications into a single distance specification.", "topics": [ "distUnion" ] }, { "page": "effectiveSampleSize", "title": "Compute the effective sample size of a match.", "topics": [ "effectiveSampleSize", "effectiveSampleSize.default", "effectiveSampleSize.factor", "effectiveSampleSize.table" ] }, { "page": "evaluate_primal", "title": "Compute value of primal problem given flows and arc costs", "topics": [ "evaluate_primal" ] }, { "page": "exactMatch", "title": "Generate an exact matching set of subproblems.", "topics": [ "exactMatch", "exactMatch,formula-method", "exactMatch,vector-method" ] }, { "page": "fill.NAs", "title": "Create missingness indicator variables and non-informatively fill in missing values", "topics": [ "fill.NAs" ] }, { "page": "findSubproblems", "title": "List subproblems of a distance", "topics": [ "findSubproblems" ] }, { "page": "fullmatch", "title": "Optimal full matching", "topics": [ "full", "fullmatch" ] }, { "page": "getMaxProblemSize", "title": "What is the maximum allowed problem size?", "topics": [ "getMaxProblemSize" ] }, { "page": "InfinitySparseMatrix-class", "title": "Objects for sparse matching problems.", "topics": [ "InfinitySparseMatrix-class" ] }, { "page": "LEMON", "title": "(Internal) Helper function for accessing algorithms in LEMON solver", "topics": [ "LEMON" ] }, { "page": "match_on-methods", "title": "Create treated to control distances for matching problems", "topics": [ "match_on", "match_on.bigglm", "match_on.formula", "match_on.function", "match_on.glm", "match_on.InfinitySparseMatrix", "match_on.matrix", "match_on.numeric" ] }, { "page": "matched", "title": "Identification of units placed into matched sets", "topics": [ "matched", "matchfailed", "unmatched" ] }, { "page": "matched.distances", "title": "Determine distances between matched units", "topics": [ "matched.distances" ] }, { "page": "maxCaliper", "title": "Find the maximum caliper width that will create a feasible problem.", "topics": [ "maxCaliper" ] }, { "page": "minmaxctlcap", "title": "Set thinning and thickening caps for full matching", "topics": [ "maxControlsCap", "minControlsCap" ] }, { "page": "mdist", "title": "(Deprecated, in favor of 'match_on') Create matching distances", "topics": [ "mdist", "mdist.bigglm", "mdist.formula", "mdist.function", "mdist.glm", "mdist.numeric", "mdist.optmatch.dlist" ] }, { "page": "minExactMatch", "title": "Find the minimal exact match factors that will be feasible for a given maximum problem size.", "topics": [ "minExactMatch" ] }, { "page": "nuclearplants", "title": "Nuclear Power Station Construction Data", "topics": [ "nuclearplants" ] }, { "page": "num_eligible_matches-methods", "title": "Returns the number of eligible matches for the distance.", "topics": [ "num_eligible_matches", "num_eligible_matches.BlockedInfinitySparseMatrix", "num_eligible_matches.InfinitySparseMatrix", "num_eligible_matches.matrix", "num_eligible_matches.optmatch.dlist" ] }, { "page": "optmatch", "title": "Optmatch Class", "topics": [ "optmatch", "optmatch-class", "summary.optmatch" ] }, { "page": "optmatch_restrictions", "title": "optmatch_restrictions", "topics": [ "optmatch_restrictions" ] }, { "page": "optmatch_same_distance", "title": "Checks if two distances are equivalent. 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Hansen, Mark Fredrickson, Josh Errickson, and Josh Buckner", "engine": "knitr::rmarkdown", "headings": [ "The R Environment", "Setup", "Outfitting your R with the proper add-ons", "Setting up the R environment for matching", "Optimal pair matching and 1:k matching", "Pair matching", "Matching with multiple controls", "Did matching work?", "Did matching balance the covariate?", "Propensity Score Matching", "Propensity score fitting in R", "Checking balance in general", "Other topics in matching", "Full matching and matching with a varying number of controls", "Subclassification before matching", "Distances", "Trying it out on your own" ], "created": "2015-12-03 16:25:30", "modified": "2023-01-31 01:10:07", "commits": 13 }, { "source": "matching-within-subgroups.Rmd", "filename": "matching-within-subgroups.html", "title": "Combining Matches Within Subgroups", "author": "Ben B. 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