<?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>Estimating Bivariate Dependency from Marginal Data</dc:title>
  <dc:title>R package ebdm version 3.0.1</dc:title>
  <dc:description>Provides statistical methods for estimating bivariate dependency (correlation) from marginal summary statistics across multiple studies. 
    The package supports three modules of bivariate joint distribution estimated from marginal summary data: (1) two binary, (2) two continuous, (3) one binary and one continuous
    These methods enable privacy-preserving joint estimation when individual-level data are unavailable.
    The approaches are detailed in Shang, Tsao, and Zhang (2025a) &lt;doi:10.48550/arXiv.2505.03995&gt; and Shang, Tsao, and Zhang (2025b) &lt;doi:10.48550/arXiv.2508.02057&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.5.0)</dc:relation>
  <dc:relation>Imports: stats</dc:relation>
  <dc:creator>Xuekui Zhang &lt;ubcxzhang@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Longwen Shang [aut],
  Min Tsao [aut],
  Xuekui Zhang [aut, cre, fnd]</dc:contributor>
  <dc:rights>GPL (&gt;= 3)</dc:rights>
  <dc:date>2026-04-23</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=ebdm</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.ebdm</dc:identifier>
</oai_dc:dc>
