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.
- Version0.4-6
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- RealVAMS citation info
- Last release04/05/2024
Documentation
Team
Andrew Karl
Jennifer Broatch
Show author detailsRolesAuthorJennifer Green
Show author detailsRolesAuthor
Insights
Last 30 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN