{ "_id": "6a269ad024555f66ed51e542", "Package": "RealVAMS", "Type": "Package", "Title": "Multivariate VAM Fitting", "Version": "0.4-6", "Date": "2024-04-05", "Authors@R": "c(person(given = c(\"Andrew\"),\nfamily = \"Karl\",\nemail=\"akarl@asu.edu\",\nrole = c(\"cre\", \"aut\"),\ncomment = c(ORCID = \"0000-0002-5933-8706\")),\nperson(given = \"Jennifer\",\nfamily = \"Broatch\",\nrole = c( \"aut\"),\n),\nperson(given = \"Jennifer\",\nfamily = \"Green\",\nrole = c( \"aut\"),\n))", "Description": "Fits a multivariate value-added model (VAM), see Broatch,\nGreen, and Karl (2018) and Broatch\nand Lohr (2012) , with normally\ndistributed test scores and a binary outcome indicator. A\npseudo-likelihood approach, Wolfinger (1993)\n, is used for the estimation of\nthis joint generalized linear mixed model. The inner loop of\nthe pseudo-likelihood routine (estimation of a linear mixed\nmodel) occurs in the framework of the EM algorithm presented by\nKarl, Yang, and Lohr (2013) .\nThis material is based upon work supported by the National\nScience Foundation under grants DRL-1336027 and DRL-1336265.", "License": "GPL-2", "LazyData": "yes", "ByteCompile": "yes", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-08 10:31:44 UTC", "User": "root" }, "Author": "Andrew Karl [cre, aut]\n(), Jennifer Broatch\n[aut], Jennifer Green [aut]", "Maintainer": "Andrew Karl ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2024-04-06 02:30:22 UTC", "RemoteUrl": "https://github.com/cran/RealVAMS", "RemoteRef": "HEAD", "RemoteSha": "2bc4b0db2619ef6f07b0b328e9070b82f7f0fd9c", "MD5sum": "676da809db8ba129553576b00979fd12", "_user": "cran", "_type": "src", "_file": "RealVAMS_0.4-6.tar.gz", "_fileid": "5a27d07f06d1c7517304b64cbf09672757080878bf7be9639e6dd2be638082f6", "_filesize": 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