Package: cIRT 1.3.2
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:
cIRT_1.3.2.tar.gz
cIRT_1.3.2.tar.gz(r-4.5-noble)cIRT_1.3.2.tar.gz(r-4.4-noble)
cIRT_1.3.2.tgz(r-4.4-emscripten)cIRT_1.3.2.tgz(r-4.3-emscripten)
cIRT.pdf |cIRT.html✨
cIRT/json (API)
NEWS
# Install 'cIRT' in R: |
install.packages('cIRT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tmsalab/cirt/issues
Pkgdown:https://tmsalab.github.io
- choice_matrix - Choice Matrix Data
- payout_matrix - Payout Matrix Data
- survey_data - Survey Data
- trial_matrix - Trial Matrix Data
Last updated 3 years agofrom:57bd4b161c. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 27 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 27 2024 |
Exports:center_matrixcIRTdirect_sumGenerate_ChoiceprobitHLMriwishartrmvnormrwishartTotal_TabulateTwoPLChoicemcmc
Dependencies:RcppRcppArmadillo
Estimating the Model in the Paper
Rendered fromEstimating-the-Model-in-the-Paper.Rmd
usingknitr::rmarkdown
on Nov 27 2024.Last update: 2020-03-23
Started: 2016-04-13
Package Overview
Rendered fromPackage-Overview.Rmd
usingknitr::rmarkdown
on Nov 27 2024.Last update: 2022-02-21
Started: 2016-04-13
Simulation Study with cIRT
Rendered fromSimulation-Study-with-cIRT.Rmd
usingknitr::rmarkdown
on Nov 27 2024.Last update: 2020-03-23
Started: 2016-04-13
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 |