RealVAMS: Multivariate VAM Fitting

Fits a multivariate value-added model (VAM), see 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. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.

Version: 0.3-3
Depends: R (≥ 3.0.0), Matrix
Imports: numDeriv, Rcpp (≥ 0.11.2), methods, stats, utils, grDevices, graphics
LinkingTo: Rcpp, RcppArmadillo
Published: 2017-03-14
Author: Andrew T. Karl, Jennifer Broatch, and Jennifer Green
Maintainer: Andrew Karl <akarl at asu.edu>
License: GPL-2
NeedsCompilation: yes
Materials: NEWS
CRAN checks: RealVAMS results

Downloads:

Reference manual: RealVAMS.pdf
Package source: RealVAMS_0.3-3.tar.gz
Windows binaries: r-devel: RealVAMS_0.3-3.zip, r-release: RealVAMS_0.3-3.zip, r-oldrel: RealVAMS_0.3-3.zip
OS X Mavericks binaries: r-release: RealVAMS_0.3-3.tgz, r-oldrel: RealVAMS_0.3-3.tgz
Old sources: RealVAMS archive

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