RealVAMS

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.