<?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>Synthetic Data Integration</dc:title>
  <dc:title>R package SynDI version 0.1.0</dc:title>
  <dc:description>Regression inference for multiple populations by integrating 
    summary-level data using stacked imputations. Gu, T., Taylor, J.M.G. and 
    Mukherjee, B. (2021) A synthetic data integration framework to leverage 
    external summary-level information from heterogeneous populations 
    &lt;arXiv:2106.06835&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.6.0)</dc:relation>
  <dc:relation>Imports: mice, magrittr, dplyr, StackImpute, arm, boot, broom, mvtnorm,
randomForest, MASS, knitr</dc:relation>
  <dc:relation>Suggests: markdown</dc:relation>
  <dc:creator>Michael Kleinsasser &lt;mkleinsa@umich.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Tian Gu [aut],
  Jeremy M.G. Taylor [aut],
  Bhramar Mukherjee [aut],
  Michael Kleinsasser [cre]</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2022-05-25</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=SynDI</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.SynDI</dc:identifier>
</oai_dc:dc>
