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GPvam: Maximum Likelihood Estimation of Multiple Membership Mixed
Models Used in Value-Added Modeling
An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects.
| Version: |
3.2-0 |
| Depends: |
R (≥ 3.2.0), Matrix |
| Imports: |
numDeriv, rlang, Rcpp (≥ 0.11.2), graphics, grDevices, methods, stats, utils, ggplot2, patchwork, MASS |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Published: |
2024-12-12 |
| DOI: |
10.32614/CRAN.package.GPvam |
| Author: |
Andrew Karl  [cre,
aut],
Yan Yang [aut],
Sharon Lohr [aut] |
| Maintainer: |
Andrew Karl <akarl at asu.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| CRAN checks: |
GPvam results |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=GPvam
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.