CRAN/E | hIRT

hIRT

Hierarchical Item Response Theory Models

Installation

About

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.

github.com/xiangzhou09/hIRT
Bug report File report

Key Metrics

Version 0.3.0
R ≥ 3.4.0
Published 2020-03-26 1490 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks hIRT results

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Maintainer

Maintainer

Xiang Zhou

xiang_zhou@fas.harvard.edu

Authors

Xiang Zhou

aut / cre

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

hIRT archive

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