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RealVAMS: Multivariate VAM Fitting

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 ORCID iD [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:

Reference manual: RealVAMS.pdf

Downloads:

Package source: RealVAMS_0.4-6.tar.gz
Windows binaries: r-devel: RealVAMS_0.4-6.zip, r-release: RealVAMS_0.4-6.zip, r-oldrel: RealVAMS_0.4-6.zip
macOS binaries: r-release (arm64): RealVAMS_0.4-6.tgz, r-oldrel (arm64): RealVAMS_0.4-6.tgz, r-release (x86_64): RealVAMS_0.4-6.tgz, r-oldrel (x86_64): RealVAMS_0.4-6.tgz
Old sources: RealVAMS archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RealVAMS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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