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: 3.1-0
Depends: R (≥ 3.2.0), Matrix
Imports: numDeriv, Rcpp (≥ 0.11.2), graphics, grDevices, methods, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Published: 2024-04-05
DOI: 10.32614/CRAN.package.GPvam
Author: Andrew Karl ORCID iD [cre, aut], Yan Yang [aut], Sharon Lohr [aut]
Maintainer: Andrew Karl <akarl at>
License: GPL-2
NeedsCompilation: yes
Materials: NEWS
CRAN checks: GPvam results


Reference manual: GPvam.pdf


Package source: GPvam_3.1-0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): GPvam_3.1-0.tgz, r-oldrel (arm64): GPvam_3.1-0.tgz, r-release (x86_64): GPvam_3.1-0.tgz, r-oldrel (x86_64): GPvam_3.1-0.tgz
Old sources: GPvam archive


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