hlt: Higher-Order Item Response Theory
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 |
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