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 [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.