Integrate Item Response Theory (IRT) and Federated Learning to estimate traditional IRT models, including the 2-Parameter Logistic (2PL) and the Graded Response Models, with enhanced privacy. It allows for the estimation in a distributed manner without compromising accuracy. A user-friendly 'shiny' application is included.
| Version: | 1.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | purrr,pracma,shiny,httr,callr,DT,ggplot2,shinyjs |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2024-09-28 |
| DOI: | 10.32614/CRAN.package.FedIRT |
| Author: | Biying Zhou [cre], Feng Ji [aut] |
| Maintainer: | Biying Zhou <zby.zhou at mail.utoronto.ca> |
| License: | MIT + fileLICENSE |
| NeedsCompilation: | no |
| CRAN checks: | FedIRT results |
| Reference manual: | FedIRT.html ,FedIRT.pdf |
| Package source: | FedIRT_1.1.0.tar.gz |
| Windows binaries: | r-devel:FedIRT_1.1.0.zip, r-release:FedIRT_1.1.0.zip, r-oldrel:FedIRT_1.1.0.zip |
| macOS binaries: | r-release (arm64):FedIRT_1.1.0.tgz, r-oldrel (arm64):FedIRT_1.1.0.tgz, r-release (x86_64):FedIRT_1.1.0.tgz, r-oldrel (x86_64):FedIRT_1.1.0.tgz |
| Old sources: | FedIRT archive |
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