Package: hIRT 0.4.0

hIRT: Hierarchical Item Response Theory Models

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.

Authors:Xiang Zhou [aut, cre]

hIRT_0.4.0.tar.gz
hIRT_0.4.0.zip(r-4.5)hIRT_0.4.0.zip(r-4.4)
hIRT_0.4.0.tgz(r-4.5-any)hIRT_0.4.0.tgz(r-4.4-any)
hIRT_0.4.0.tar.gz(r-4.5-noble)hIRT_0.4.0.tar.gz(r-4.4-noble)
hIRT_0.4.0.tgz(r-4.4-emscripten)
hIRT.pdf |hIRT.html✨
hIRT/json (API)
NEWS

# Install 'hIRT' in R:

install.packages('hIRT', repos = c('https://xiangzhou09.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/xiangzhou09/hirt/issues

Datasets:

nes_econ2008 - Public Attitudes on Economic Issues in ANES 2008

On CRAN:

3.82 score 12 stars 11 scripts 201 downloads 9 exports 89 dependencies

Last updated 3 years agofrom:b33d90f132. Checks:6 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Feb 06 2025
R-4.5-win	OK	Feb 06 2025
R-4.5-mac	OK	Feb 06 2025
R-4.5-linux	OK	Feb 06 2025
R-4.4-win	OK	Feb 06 2025
R-4.4-mac	OK	Feb 06 2025

Exports:coef_item coef_mean coef_var hgrm hgrm2 hgrmDIF hltm hltm2 latent_scores

Dependencies:admisc backports base64enc bslib cachem checkmate cli cluster codetools colorspace cpp11 crayon data.table digest evaluate expm fansi farver fastmap fontawesome foreign Formula fs generics ggplot2 glue gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets isoband jquerylib jsonlite knitr labeling lattice lifecycle lobstr ltm magrittr MASS Matrix MatrixModels memoise mgcv mime msm multcomp munsell mvtnorm nlme nnet pillar pkgconfig polspline polycor prettyunits pryr quantreg R6 rappdirs RColorBrewer Rcpp rlang rmarkdown rms rpart rstudioapi sandwich sass scales SparseM stringi stringr survival TH.data tibble tinytex utf8 vctrs viridis viridisLite withr xfun yaml zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Parameter Estimates from Hierarchical IRT Models.	coef_item coef_mean coef_var
Fitting Hierarchical Graded Response Models (for Ordinal Responses)	hgrm
Hierarchical Graded Response Models with Known Item Parameters	hgrm2
Hierarchical Graded Response Models with Differential Item Functioning	hgrmDIF
Fitting Hierarchical Latent Trait Models (for Binary Responses).	hltm
Hierarchical Latent Trait Models with Known Item Parameters.	hltm2
Estimates of Latent Preferences/Abilities	latent_scores
Public Attitudes on Economic Issues in ANES 2008	nes_econ2008
Printing an object of class 'hIRT'	print.hIRT
Summarizing Hierarchical Item Response Theory Models	print.summary_hIRT summary.hIRT