Package: cIRT 1.3.2

James Joseph Balamuta

cIRT: Choice Item Response Theory

Jointly model the accuracy of cognitive responses and item choices within a Bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.

Authors:Steven Andrew Culpepper [aut, cph], James Joseph Balamuta [aut, cph, cre]

cIRT_1.3.2.tar.gz
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cIRT_1.3.2.tgz(r-4.4-x86_64)cIRT_1.3.2.tgz(r-4.4-arm64)cIRT_1.3.2.tgz(r-4.3-x86_64)cIRT_1.3.2.tgz(r-4.3-arm64)
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cIRT.pdf |cIRT.html✨
cIRT/json (API)
NEWS

# Install 'cIRT' in R:

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

Bug tracker:https://github.com/tmsalab/cirt/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

choice_matrix - Choice Matrix Data
payout_matrix - Payout Matrix Data
survey_data - Survey Data
trial_matrix - Trial Matrix Data

On CRAN:

armadillo bayesian choice cognitive-diagnostic-models gibbs-sampling item-response-theory rcpparmadillo

10 exports 4 stars 5.14 score 2 dependencies 23 scripts 260 downloads

Last updated 3 years agofrom:84f92aa37c. Checks:OK: 1 NOTE: 8. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 01 2024
R-4.5-win-x86_64	NOTE	Oct 01 2024
R-4.5-linux-x86_64	NOTE	Oct 01 2024
R-4.4-win-x86_64	NOTE	Oct 01 2024
R-4.4-mac-x86_64	NOTE	Oct 01 2024
R-4.4-mac-aarch64	NOTE	Oct 01 2024
R-4.3-win-x86_64	NOTE	Oct 01 2024
R-4.3-mac-x86_64	NOTE	Oct 01 2024
R-4.3-mac-aarch64	NOTE	Oct 01 2024

Exports:center_matrix cIRT direct_sum Generate_Choice probitHLM riwishart rmvnorm rwishart Total_Tabulate TwoPLChoicemcmc

Dependencies:Rcpp RcppArmadillo

Estimating the Model in the Paper

Rendered fromEstimating-the-Model-in-the-Paper.Rmdusingknitr::rmarkdownon Oct 01 2024.

Last update: 2020-03-22
Started: 2016-04-13

Package Overview

Rendered fromPackage-Overview.Rmdusingknitr::rmarkdownon Oct 01 2024.

Last update: 2022-02-21
Started: 2016-04-13

Simulation Study with cIRT

Rendered fromSimulation-Study-with-cIRT.Rmdusingknitr::rmarkdownon Oct 01 2024.

Last update: 2020-03-22
Started: 2016-04-13

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
cIRT: Choice Item Response Theory	cIRT-package _PACKAGE
Center a Matrix	center_matrix
Choice Matrix Data	choice_matrix
Generic Implementation of Choice IRT MCMC	cIRT
Direct Sum of Matrices	direct_sum
Generate Observed Data from choice model	Generate_Choice
Payout Matrix Data	payout_matrix
Probit Hierarchical Level Model	probitHLM
Generate Random Inverse Wishart Distribution	riwishart
Generate Random Multivariate Normal Distribution	rmvnorm
Generate Random Wishart Distribution	rwishart
Survey Data	survey_data
Calculate Tabulated Total Scores	Total_Tabulate
Trial Matrix Data	trial_matrix
Two Parameter Choice IRT Model MCMC	TwoPLChoicemcmc