RealVAMS (0.4-3)

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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.

Maintainer: Andrew Karl
Author(s): Andrew T. Karl, Jennifer Broatch, and Jennifer Green

License: GPL-2

Uses: Matrix, numDeriv, Rcpp

Released 9 months ago.

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