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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 |
Maintainer: | Andrew Karl <akarl at asu.edu> |
License: | GPL-2 |
NeedsCompilation: | yes |
Citation: | RealVAMS citation info |
Materials: | NEWS |
CRAN checks: | RealVAMS results |
Reference manual: | RealVAMS.pdf |
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 |
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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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