Fits a multivariate value-added model (VAM), see Broatch, Green, and Karl (2018)
Version 0.4-3: 2019-04-22 - Added the joint covariance matrix, C, of the estimated fixed effects and predicted random effects to the output. See Henderson (1975). - Paper reference added to manuals and to CITATION file.
Version 0.4-0: 2017-08-13 - New arguments added to the RealVAMS function -- independent.responses defaults to FALSE. If TRUE, this option will model the responses independently by fixing the covariances in G at 0 as well as the covariances in the last row/column of R. The resulting estimates are the same as those that would be obtained by modelling the test scores in package GPvam (with REML=FALSE) and modelling the binary respones in SAS GLIMMIX (RealVAMS has been validated against these programs). -- cpp.benchmark defaults to FALSE. If TRUE, this option will perform the calculations shown in equation (16) of Karl, Yang, Lohr (2013) using both R and the embedded C++ code to demonstrate the time savings of using C++. A summary table is printed at the end. - The functions in the code of the file vp_cp (the estimation routine) have been commented to explain their purpose and to reference which equations from Karl, Yang, Lohr (2013) or Wolfinger and O'Connell (1993) they represent
Version 0.3-3: 2017-03-02 - Add generic summary, plot, and print functions. - Added detail to documentation for the RealVAMS function - Reformatted user manual documentation for simulated data - Renamed some of the elements of the RealVAMS class
Version 0.3-2: 2015-07-19 - Minor updates to package structure to match new CRAN requirements.
Version 0.3-1: 2014-11-01 - First public release.