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) . In addition, the package contains the datasets used within the analysis of the paper.


cIRT 1.2.1

  • Added src/init.c for R 3.4 compatibility
  • Added GitHub project page link

cIRT 1.2.0

  • Added two vignettes that cover the model estimation and simulation results in the package.
  • Added a file to track changes to the package.

cIRT 1.1.0

  • Adds two columns to choice matrix: hard_q_id and easy_q_id.

cIRT 1.0.0

Modeling Framework

  • Implementation of the hiercharical framework described in "A Hierarchical Model for Accuracy and Choice on Standardized Tests"
  • Specifically, a choice inclusive Probit HLM and a Two Parameter Ogive Model.

C++ Functions

  • Random Number Generation for the following distributions: Wishart, Inverse Wishart, and Multivariate Normal
  • Matrix Centering
  • Direct Sum calculation


  • Student Performance on Revised Purdue Spatial Visualization Test (Revised PSVT:R) by Yoon, 2011 in trial_matrix
  • The choices students made among items presented to them in choice_matrix
  • The end payout results for students based on their choices in payout_matrix
  • One additional data set exists containing the student's sex response in survey_data

Reference manual

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1.2.1 by James Balamuta, a year ago

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Browse source code at

Authors: Steve Culpepper [aut, cph], James Balamuta [aut, cre, ctb, com, cph]

Documentation:   PDF Manual  

Task views: Psychometric Models and Methods

GPL-3 license

Imports Rcpp

Suggests knitr, rmarkdown

Linking to Rcpp, RcppArmadillo

See at CRAN