{ "_id": "6a51697d9b92047c28d507a5", "Package": "ctreeMI", "Title": "Conditional Inference Trees with Stacked Multiple Imputation", "Version": "0.1.0", "Authors@R": "person(\"Phillip\", \"Sherlock\",\nemail = \"phillip.sherlock@ufl.edu\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0433-3681\"))", "Description": "Implements the stacked-imputation workflow for conditional\ninference trees ('ctree') described in Sherlock et al. (2026)\n. When data contain missing\nvalues, multiply imputed datasets (e.g., from 'mice') are\nstacked vertically and a single 'ctree' is fit on the combined\ndata. To correct for the artificially inflated sample size\nintroduced by stacking, the pruning significance threshold is\ndivided by the number of imputations M (the Stack/M\ncorrection), producing a conservative but interpretable single\ntree that incorporates imputation uncertainty without requiring\npooling of structurally different trees. Also exports\nstack_imputations() and rescale_alpha() as standalone\nutilities. The underlying 'ctree' algorithm is provided by\n'partykit' (Hothorn & Zeileis, 2015; Hothorn, Hornik & Zeileis,\n2006 ).", "License": "GPL (>= 3)", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "URL": "https://github.com/Phillip-Sherlock/ctreeMI", "BugReports": "https://github.com/Phillip-Sherlock/ctreeMI/issues", "NeedsCompilation": "no", "Packaged": { "Date": "2026-07-10 21:49:00 UTC", "User": "root" }, "Author": "Phillip Sherlock [aut, cre] (ORCID:\n)", "Maintainer": "Phillip Sherlock ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-07-10 19:00:02 UTC", "RemoteUrl": "https://github.com/cran/ctreeMI", "RemoteRef": "HEAD", "RemoteSha": "08c92d62de0821666f4e59573843b05266436384", "_user": "cran", "_type": "src", "_file": "ctreeMI_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/840832fd223a37be158ea7ed41ecb41070ea257dfb77b83a98e4ab09067fe693", "_filesize": 146220, "_sha256": 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