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

Documentation:

Reference manual:

hlt.pdf

Downloads:

Package source:	hlt_1.3.1.tar.gz
Windows binaries:	r-devel: hlt_1.3.1.zip, r-release: hlt_1.3.1.zip, r-oldrel: hlt_1.3.1.zip
macOS binaries:	r-release (arm64): hlt_1.3.1.tgz, r-oldrel (arm64): hlt_1.3.1.tgz, r-release (x86_64): hlt_1.3.1.tgz, r-oldrel (x86_64): hlt_1.3.1.tgz

Linking:

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