Multivariate VAM Fitting

Fits a multivariate value-added model (VAM), see Broatch, Green, and Karl (2018) and Broatch and Lohr (2012) , with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) , 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) . This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.


Reference manual

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install.packages("RealVAMS")

0.5.0 by Andrew Karl, 16 days ago


Browse source code at https://github.com/cran/RealVAMS


Authors: Andrew Karl [cre, aut] , Jennifer Broatch [aut] , Jennifer Green [aut]


Documentation:   PDF Manual  


GPL-2 license


Imports numDeriv, Rcpp, methods, stats, utils, grDevices, graphics

Depends on Matrix

Suggests testthat, roxygen2

Linking to Rcpp, RcppArmadillo


See at CRAN