RealVAMS: Multivariate VAM Fitting
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 [cre, aut], Jennifer Broatch [aut], Jennifer Green [aut] |
| Maintainer: | Andrew Karl <akarl at asu.edu> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| Citation: | RealVAMS citation info |
| Materials: | NEWS |
| CRAN checks: | RealVAMS results |
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