cIRT 1.3.3

Changes

• Added explicit dependencies on R (>= 4.3.0), Rcpp (>= 1.1.0), and RcppArmadillo (>= 15.0.2-2)
• Removed CXX11 from src/Makevars and src/Makevars.win to avoid potential compilation issues with newer versions of Armadillo through RcppArmadillo.
• Switched README.Rmd to README.qmd to use Quarto for rendering.
• Addressed deprecation warning of "replace conv_to<...>::from(X) with as_scalar(X)" in src/project_source.cpp by using arma::as_scalar(...) instead of conv_to<double>::from(...).
• Fixed CITATION file to use c() instead of personList() and bibentry() to avoid CRAN check notes.
• Updated GitHub Action workflows.

cIRT 1.3.2

Changes

• Fix use of 'middle' argument by using 'given' in person(). (#8)
• Bump requirements to using R 4.0.0 , Rcpp 1.0.8, and RcppArmadillo 10.8.1 or above. (#8)

cIRT 1.3.1

Changes

• Added LazyData: true to DESCRIPTION to match with how the data documentation is called. (#3)

Documentation

• Added a pkgdown website that deploys to https://tmsalab.github.io/cIRT/. (#3)

Deployment

• Switched from Travis-CI to GitHub Actions for R. (#5)

cIRT 1.3.0

Changes

• Updated package dependencies
• Enabled C++11 and OpenMP.
• Switched to allowing Rcpp to handle native registration

Bugfix

• Addressed issues in the choice generation procedure.

Documentation

• Improved in-line documentation.
• Added Authors’ ORCIDs to DESCRIPTION.

Testing

• Enabled TMSA Lab’s configuration for Travis-CI.

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 NEWS.md 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 hierarchical 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

Data

• 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