Fits a multivariate value-added model (VAM), see Broatch, Green, and Karl (2018) <doi:10.32614/RJ-2018-033> and Broatch and Lohr (2012) <doi:10.3102/1076998610396900>, with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) <doi:10.1080/00949659308811554>, is used for the estimation of this joint generalized linear mixed model. The inner loop of the pseudo-likelihood routine (estimation of a linear mixed model) occurs in the framework of the EM algorithm presented by Karl, Yang, and Lohr (2013) <doi:10.1016/j.csda.2012.10.004>. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.
Version: 0.4-6 Depends: R (≥ 3.0.0), Matrix Imports: numDeriv, Rcpp (≥ 0.11.2), methods, stats, utils, grDevices, graphics LinkingTo: Rcpp, RcppArmadillo Published: 2024-04-05 DOI: 10.32614/CRAN.package.RealVAMS Author: Andrew Karl [cre, aut], Jennifer Broatch [aut], Jennifer Green [aut] Maintainer: Andrew Karl <akarl at asu.edu> License: GPL-2 NeedsCompilation: yes Citation: RealVAMS citation info Materials: NEWS CRAN checks: RealVAMS results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=RealVAMS to link to this page.
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