{ "_id": "6ab4ed373d719c1f8409764a", "Package": "CARM", "Title": "Covariate-Adjusted Adaptive Randomization via\nMahalanobis-Distance", "Version": "1.1.0", "Authors@R": "c(person(given = \"Haoyu\",\nfamily = \"Yang\",\nrole = c(\"aut\"),\nemail = \"haoyuyang@ruc.edu.cn\"),\nperson(given = \"Fanglu\",\nfamily = \"Chen\",\nrole = c(\"aut\", \"cre\"),\nemail = \"chenfanglu1031@qq.com\"),\nperson(given = \"Yichen\",\nfamily = \"Qin\",\nrole = c(\"aut\"),\nemail = \"qinyn@ucmail.uc.edu\"),\nperson(given = \"Yang\",\nfamily = \"Li\",\nrole = c(\"aut\"),\nemail = \"yang.li@ruc.edu.cn\"))", "Author": "Haoyu Yang [aut], Fanglu Chen [aut, cre], Yichen Qin [aut],\nYang Li [aut]", "Maintainer": "Fanglu Chen ", "Description": "In randomized controlled trial (RCT), balancing covariate\nis often one of the most important concern. CARM package\nprovides functions to balance the covariates and generate\nallocation sequence by covariate-adjusted Adaptive\nRandomization via Mahalanobis-distance (ARM) for RCT. About\nwhat ARM is and how it works please see Y. Qin, Y. Li, W. Ma,\nH. Yang, and F. Hu (2022). \"Adaptive randomization via\nMahalanobis distance\" Statistica Sinica.\n. In addition, the package is also\nsuitable for the randomization process of multi-arm trials. For\ndetails, please see Yang H, Qin Y, Wang F, et al. (2023).\n\"Balancing covariates in multi-arm trials via adaptive\nrandomization\" Computational Statistics & Data\nAnalysis..", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "7.2.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-24 09:24:24 UTC", "User": "root" }, "Config/pak/sysreqs": "libgmp3-dev", "Repository": "https://fanglu-chen.r-universe.dev", "Date/Publication": "2024-07-29 06:43:34 UTC", "RemoteUrl": "https://github.com/fanglu-chen/carm", "RemoteRef": "HEAD", "RemoteSha": "de5d5be0c9225b092a144e9d9faf723dbadb57d5", "_user": "fanglu-chen", "_type": "src", "_file": "CARM_1.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/02dd00a8d18d158129a76982c67fad98a8edde000c86dc7be94ee8ba0eb386f6", "_filesize": 152913, "_sha256": "02dd00a8d18d158129a76982c67fad98a8edde000c86dc7be94ee8ba0eb386f6", "_expires": "2027-01-02T09:28:21.000Z", "_created": "2026-09-24T09:24:24.000Z", "_published": "2026-09-24T09:28:23.773Z", "_jobs": [ { "job": 107572807533, "time": 122, 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