{
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  "Package": "rmedsem",
  "Title": "Statistical Mediation Analysis for SEMs",
  "Version": "1.1.1",
  "Authors@R": "c(\nperson(\"Mehmet\", \"Mehmetoglu\", email=\"mehmet.mehmetoglu@ntnu.no\", role = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-6092-8551\")),\nperson(\"Matthias\", \"Mittner\", email=\"matthias.mittner@uit.no\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0205-7353\")),\nperson(\"Kjell\", \"Slupphaug\", email=\"slupphaugkjell@gmail.com\", role = c(\"aut\"),\ncomment = c(ORCID = \"0009-0005-8324-2834\"))\n)",
  "Description": "Conducts mediation analysis for structural equation models\n(SEM) estimated with 'lavaan', 'blavaan', 'cSEM', 'plssem', or\n'modsem'. Implements the Baron and Kenny (1986)\n<doi:10.1037/0022-3514.51.6.1173> and Zhao, Lynch & Chen (2010)\n<doi:10.1086/651257> approaches to determine the presence and\ntype of mediation. Supports covariance-based SEM, partial least\nsquares SEM, Bayesian SEM, and moderated mediation and mediated\nmoderation models. Tests indirect effects with the Sobel,\nDelta, Monte-Carlo, and bootstrap methods or, for Bayesian\nmodels, with posterior summaries and equal-tailed or highest\ndensity credible intervals. Reports the effect size measures\nRIT, RID, and Upsilon of Lachowicz, Preacher and Kelley (2018)\n<doi:10.1037/met0000165>. Results can be summarized, extracted\nwith standard methods such as summary(), coef() and confint(),\nand plotted.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "Date/Publication": "2026-09-17 07:51:58 UTC",
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