Package: hIRT
Type: Package
Title: Hierarchical Item Response Theory Models
Version: 0.3.0
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.
Depends: R (>= 3.4.0), stats
Imports: pryr (>= 0.1.2), rms (>= 5.1-1), ltm (>= 1.1-1), Matrix (>=
        1.2-10)
Suggests: ggplot2 (>= 2.2.1), knitr, rmarkdown
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
URL: http://github.com/xiangzhou09/hIRT
BugReports: http://github.com/xiangzhou09/hIRT
NeedsCompilation: no
Packaged: 2020-03-26 16:46:52 UTC; Xiang
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2020-03-26 17:10:02 UTC
Built: R 4.2.0; ; 2022-04-13 16:22:33 UTC; unix
