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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.4-6 |
rolling linux/jammy R-4.5 | RealVAMS_0.4-6.tar.gz |
222.0 KiB |
0.4-6 |
rolling linux/noble R-4.5 | RealVAMS_0.4-6.tar.gz |
224.9 KiB |
0.4-6 |
rolling source/ R- | RealVAMS_0.4-6.tar.gz |
70.5 KiB |
0.4-6 |
latest linux/jammy R-4.5 | RealVAMS_0.4-6.tar.gz |
222.0 KiB |
0.4-6 |
latest linux/noble R-4.5 | RealVAMS_0.4-6.tar.gz |
224.9 KiB |
0.4-6 |
latest source/ R- | RealVAMS_0.4-6.tar.gz |
70.5 KiB |
0.4-6 |
2026-04-26 source/ R- | RealVAMS_0.4-6.tar.gz |
70.5 KiB |
0.4-6 |
2026-04-23 source/ R- | RealVAMS_0.4-6.tar.gz |
70.5 KiB |
0.4-6 |
2026-04-09 windows/windows R-4.5 | RealVAMS_0.4-6.zip |
546.3 KiB |
0.4-6 |
2025-04-20 source/ R- | RealVAMS_0.4-6.tar.gz |
70.5 KiB |