Package: GPvam 3.1-2
Andrew Karl
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.
Authors:
GPvam_3.1-2.tar.gz
GPvam_3.1-2.tar.gz(r-4.5-noble)GPvam_3.1-2.tar.gz(r-4.4-noble)
GPvam_3.1-2.tgz(r-4.4-emscripten)GPvam_3.1-2.tgz(r-4.3-emscripten)
GPvam.pdf |GPvam.html✨
GPvam/json (API)
NEWS
| # Install 'GPvam' in R: |
| install.packages('GPvam', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- GPvam.benchmark - Benchmarks of the program using simulated data.
- vam_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 7 days agofrom:c7b60ef19c. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 19 2024 |
| R-4.5-linux-x86_64 | OK | Nov 19 2024 |
Exports:bias.test.customGPvamplot.GPvamprint.GPvamsummary.GPvam
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmenumDerivpatchworkpillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling | GPvam-package |
| Permutation Tests for Fixed Effects Bias Assessment | bias.test.custom |
| Internal G-side effects function | GP.csh |
| Internal R-side effects function | GP.un |
| Fitting the Generalized and Variable Persistence Models | GPvam |
| Benchmarks of the program using simulated data. | GPvam.benchmark |
| Plot method for GPvam | plot.GPvam |
| print.GPvam print.summary.GPvam | |
| Internal R-side effects function for reduced GP model | rGP.un |
| Summary | summary.GPvam |
| Simulated Data | vam_data |
| Internal R-side effects function for the variable persistence model. | VP.CP.ZP.un |
