Higher-order latent trait theory (item response theory). We implement the generalized partial credit model with a second-order latent trait structure. Latent regression can be done on the second-order latent trait. For a pre-print of the methods, see, "Latent Regression in Higher-Order Item Response Theory with the R Package hlt" <https://mkleinsa.github.io/doc/hlt_proof_draft_brmic.pdf>.
Version: 1.3.1 Depends: R (≥ 3.5.0) Imports: Rcpp (≥ 1.0.8), RcppDist, RcppProgress, tidyr, ggplot2, truncnorm, foreach, doParallel LinkingTo: Rcpp, RcppDist, RcppProgress Published: 2022-08-22 DOI: 10.32614/CRAN.package.hlt Author: Michael Kleinsasser [aut, cre] Maintainer: Michael Kleinsasser <mjkleinsa at gmail.com> BugReports: https://github.com/mkleinsa/hlt/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/mkleinsa/hlt NeedsCompilation: yes Materials: README CRAN checks: hlt results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=hlt to link to this page.
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