{ "_id": "6ac22548773a0037682c2a77", "Package": "ccwr", "Title": "Clone-Censor-Weight Methods for Target Trial Emulation", "Version": "0.0.1", "Authors@R": "c(\nperson(\"Sang Ho\", \"Park\", email = \"shstat1729@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Youngrok\", \"Lee\", role = \"aut\"),\nperson(\"Jihyeon\", \"Baek\", role = \"aut\"),\nperson(\"Hye Won\", \"Yang\", role = \"aut\"),\nperson(\"Donghoon\", \"Jeong\", role = \"aut\")\n)", "Description": "Provides methods for clone-censor-weight analyses that\nemulate target trials with grace-period treatment strategies\nusing observational time-to-event data. Tools clone\nparticipants across strategies, apply strategy-specific\nartificial censoring, and estimate inverse probability of\ncensoring weights using pooled logistic or Cox models, fit\nweighted outcome models, and obtain subject-level bootstrap\nconfidence intervals by repeating the complete analysis. The\nmethods are described by Maringe et al. (2020)\n and Gaber et al. (2024)\n.", "License": "MIT + file LICENSE", "Copyright": "See inst/COPYRIGHTS", "URL": "https://github.com/CausalInferenceLab/ccwr", "BugReports": "https://github.com/CausalInferenceLab/ccwr/issues", "Encoding": "UTF-8", "Config/testthat/edition": "3", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "8.0.0", "LazyData": "true", "VignetteBuilder": "knitr", "Repository": "https://causalinferencelab.r-universe.dev", "Date/Publication": "2026-08-20 21:42:58 UTC", "RemoteUrl": "https://github.com/causalinferencelab/ccwr", "RemoteRef": "HEAD", "RemoteSha": "d27a4e8a481c8621339ffaac2c069b223996c96f", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-04 10:03:09 UTC", "User": "root" }, "Author": "Sang Ho Park [aut, cre],\nYoungrok Lee [aut],\nJihyeon Baek [aut],\nHye Won Yang [aut],\nDonghoon Jeong [aut]", "Maintainer": "Sang Ho Park ", "_user": "causalinferencelab", "_type": "src", "_file": "ccwr_0.0.1.tar.gz", "_fileid": 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