<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Multiple Imputation Using MICE and Random Forest</dc:title>
  <dc:title>R package CALIBERrfimpute version 1.0-8</dc:title>
  <dc:subject>CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData)</dc:subject>
  <dc:description>Functions to impute using random forest under full conditional specifications (multivariate imputation by chained equations). The methods are described in Shah and others (2014) &lt;doi:10.1093/aje/kwt312&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: mice (&gt;= 2.20)</dc:relation>
  <dc:relation>Imports: mvtnorm, randomForest</dc:relation>
  <dc:relation>Suggests: missForest, rpart, survival, xtable, ranger</dc:relation>
  <dc:creator>Anoop Shah &lt;anoop@doctors.org.uk&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Anoop Shah [aut, cre],
  Jonathan Bartlett [ctb],
  Harry Hemingway [ths],
  Owen Nicholas [ths],
  Aroon Hingorani [ths]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2026-02-23</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=CALIBERrfimpute</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.CALIBERrfimpute</dc:identifier>
</oai_dc:dc>
