Package: hIRT
Type: Package
Title: Hierarchical Item Response Theory Models
Version: 0.4.0
Authors@R: person("Xiang", "Zhou", email = "xiang_zhou@fas.harvard.edu",
  role = c("aut", "cre"))
Description: Implementation of a class of hierarchical item response
        theory (IRT) models where both the mean and the variance of
        latent preferences (ability parameters) may depend on observed
        covariates. The current implementation includes both the
        two-parameter latent trait model for binary data and the graded
        response model for ordinal data. Both are fitted via the
        Expectation-Maximization (EM) algorithm. Asymptotic standard
        errors are derived from the observed information matrix. See
        Zhou (2019) <doi:10.1017/pan.2018.63> for details.
Depends: R (>= 3.4.0), stats
Imports: rms (>= 5.1-1), ltm (>= 1.1-1), Matrix (>= 1.2-10)
Suggests: ggplot2
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
URL: https://github.com/xiangzhou09/hIRT
BugReports: https://github.com/xiangzhou09/hIRT/issues
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev
Repository: https://xiangzhou09.r-universe.dev
Date/Publication: 2026-09-28 14:06:06 UTC
RemoteUrl: https://github.com/xiangzhou09/hirt
RemoteRef: HEAD
RemoteSha: c61f49acde5263f32b7156f923c572144e084e79
NeedsCompilation: no
Packaged: 2026-09-29 16:53:27 UTC; root
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>