GPvam: Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling

An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects.

Version: 3.0-5
Depends: R (≥ 3.2.0), Matrix
Imports: numDeriv, Rcpp (≥ 0.11.2), graphics, grDevices, methods, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Published: 2018-04-18
Author: Andrew Karl, Yan Yang, and Sharon Lohr
Maintainer: Andrew Karl <akarl at asu.edu>
License: GPL-2
NeedsCompilation: yes
Materials: NEWS
CRAN checks: GPvam results

Downloads:

Reference manual: GPvam.pdf
Package source: GPvam_3.0-5.tar.gz
Windows binaries: r-devel: GPvam_3.0-5.zip, r-devel-gcc8: GPvam_3.0-5.zip, r-release: GPvam_3.0-5.zip, r-oldrel: GPvam_3.0-5.zip
OS X binaries: r-release: GPvam_3.0-5.tgz, r-oldrel: GPvam_3.0-5.tgz
Old sources: GPvam archive

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