<?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>Multivariate Difference Between Two Groups</dc:title>
  <dc:title>R package multid version 1.0.2</dc:title>
  <dc:description>Estimation of multivariate differences between two groups (e.g., multivariate sex differences) with regularized regression methods and predictive approach. See Ilmarinen et al. (2023) &lt;doi:10.1177/08902070221088155&gt;. Deconstructing difference score correlations (e.g., gender-equality paradox), see Ilmarinen &amp; Lönnqvist (2024) &lt;doi:10.1037/pspp0000508&gt;.
    Includes also tools that help in understanding difference score reliability, conditional intra-class correlations, tail-dependency, and heterogeneity of variance estimates. Package development was supported by the Academy of Finland research grant 338891.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.5)</dc:relation>
  <dc:relation>Imports: dplyr (&gt;= 1.0.7), glmnet (&gt;= 4.1.2), stats (&gt;= 4.0.2), pROC
(&gt;= 1.18.0), lavaan (&gt;= 0.6.9), emmeans (&gt;= 1.6.3), lme4 (&gt;=
1.1.27.1), quantreg (&gt;= 5.88), lmerTest (&gt;= 3.1.3), ggpubr (&gt;=
0.6.0), ggplot2 (&gt;= 3.4.4), rlang (&gt;= 1.1.6)</dc:relation>
  <dc:relation>Suggests: knitr (&gt;= 1.39), rmarkdown (&gt;= 2.14), overlapping (&gt;= 1.7),
rio (&gt;= 0.5.29)</dc:relation>
  <dc:creator>Ville-Juhani Ilmarinen &lt;vj.ilmarinen@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Ville-Juhani Ilmarinen [aut, cre] (ORCID:
    &lt;https://orcid.org/0000-0001-9493-379X&gt;)</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2025-09-23</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=multid</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.multid</dc:identifier>
</oai_dc:dc>
