doi:10.1093/jssam/smz027>. Includes functionality for data fit with the classic item response methods including the latent trait model, Birnbaum's three parameter model, the graded response, and the generalized partial credit model. Additionally, includes several ability parameter estimation and item selection routines. During item selection, all calculations are done in compiled C++ code.">

catSurv: Computerized Adaptive Testing for Survey Research (original) (raw)

Provides methods of computerized adaptive testing for survey researchers. See Montgomery and Rossiter (2020) <doi:10.1093/jssam/smz027>. Includes functionality for data fit with the classic item response methods including the latent trait model, Birnbaum's three parameter model, the graded response, and the generalized partial credit model. Additionally, includes several ability parameter estimation and item selection routines. During item selection, all calculations are done in compiled C++ code.

Version: 1.5.0
Depends: ltm (≥ 1.1.1), R (≥ 3.4)
Imports: jsonlite, methods, stats, plyr, Rcpp (≥ 1.0.1), RcppParallel
LinkingTo: BH (≥ 1.69.0.1), Rcpp (≥ 1.0.1), RcppArmadillo, RcppGSL (≥ 0.3.6), RcppParallel
Suggests: catIrt (≥ 0.5.0), catR (≥ 3.16), testthat (≥ 2.0.1)
Published: 2022-12-03
DOI: 10.32614/CRAN.package.catSurv
Author: Jacob Montgomery [aut], Erin Rossiter [aut, cre]
Maintainer: Erin Rossiter
BugReports: https://github.com/erossiter/catSurv/issues
License: GPL-3
NeedsCompilation: yes
SystemRequirements: C++11, GNU make
Materials: NEWS
CRAN checks: catSurv results

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