{
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  "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 <chenfanglu1031@qq.com>",
  "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<doi:10.5705/ss.202020.0440>. 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.<doi:10.1016/j.csda.2022.107642>.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
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    "User": "root"
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  "Repository": "https://fanglu-chen.r-universe.dev",
  "Date/Publication": "2024-07-29 06:43:34 UTC",
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      "title": "Adaptive Randomization via Mahalanobis Distance",
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