Package: RealVAMS 0.4-6
Andrew Karl
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.
Authors:
RealVAMS_0.4-6.tar.gz
RealVAMS_0.4-6.tar.gz(r-4.5-noble)RealVAMS_0.4-6.tar.gz(r-4.4-noble)
RealVAMS_0.4-6.tgz(r-4.4-emscripten)RealVAMS_0.4-6.tgz(r-4.3-emscripten)
RealVAMS.pdf |RealVAMS.html✨
RealVAMS/json (API)
NEWS
| # Install 'RealVAMS' in R: |
| install.packages('RealVAMS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- example.outcome.data - Simulated Data
- example.score.data - Simulated Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:2bc4b0db26. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 02 2024 |
| R-4.5-linux-x86_64 | OK | Dec 02 2024 |
Exports:RealVAMS
Dependencies:latticeMatrixnumDerivRcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Multivariate VAM Fitting | RealVAMS-package |
| Simulated Data | example.outcome.data |
| Simulated Data | example.score.data |
| Plot method for RealVAMS | plot.RealVAMS |
| print.RealVAMS print.summary.RealVAMS | |
| Internal function | R_mstep2 |
| Multivariate VAM Fitting | RealVAMS |
| Internal function | REML_Rm |
| Summary | summary.RealVAMS |
| Internal function | vp_cp |
