Package: RealVAMS 0.4-6

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:Andrew Karl [cre, aut], Jennifer Broatch [aut], Jennifer Green [aut]

RealVAMS_0.4-6.tar.gz
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RealVAMS_0.4-6.tgz(r-4.4-x86_64)RealVAMS_0.4-6.tgz(r-4.4-arm64)RealVAMS_0.4-6.tgz(r-4.3-x86_64)RealVAMS_0.4-6.tgz(r-4.3-arm64)
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RealVAMS.pdf |RealVAMS.html
RealVAMS/json (API)
NEWS

# Install 'RealVAMS' in R:
install.packages('RealVAMS', repos = c('https://akarl46556.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 6 scripts 193 downloads 1 exports 5 dependencies

Last updated 8 months agofrom:2bc4b0db26. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-win-x86_64OKNov 04 2024
R-4.5-linux-x86_64OKNov 04 2024
R-4.4-win-x86_64OKNov 04 2024
R-4.4-mac-x86_64OKNov 04 2024
R-4.4-mac-aarch64OKNov 04 2024
R-4.3-win-x86_64OKNov 04 2024
R-4.3-mac-x86_64OKNov 04 2024
R-4.3-mac-aarch64OKNov 04 2024

Exports:RealVAMS

Dependencies:latticeMatrixnumDerivRcppRcppArmadillo

Readme and manuals

Help Manual

Help pageTopics
Multivariate VAM FittingRealVAMS-package
Simulated Dataexample.outcome.data
Simulated Dataexample.score.data
Plot method for RealVAMSplot.RealVAMS
Printprint.RealVAMS print.summary.RealVAMS
Internal functionR_mstep2
Multivariate VAM FittingRealVAMS
Internal functionREML_Rm
Summarysummary.RealVAMS
Internal functionvp_cp