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ForceChoice: Forced-Choice Modeling Based on Item Response Theory and Cognitive Diagnostic Models

Fits, simulates, and evaluates forced-choice and traditional item response theory (IRT) models for noncognitive assessment. Eight model families are supported, spanning dominance (multidimensional IRT (MIRT) 1PL–4PL; multidimensional generalized partial credit model (MGPCM)), ideal-point unfolding (multidimensional generalized graded unfolding model (MGGUM)), and forced-choice designs (forced-choice multidimensional IRT (FCMIRT), forced-choice generalized graded unfolding model (FCGGUM), Thurstonian IRT (TIRT), forced-choice diagnostic classification model (FCDCM), forced-choice generalized deterministic inputs, noisy "and" gate model (FCGDINA)) that mitigate response biases such as acquiescence and social desirability. Core estimation backends include full Bayesian inference via Hamiltonian Monte Carlo (Stan) and a fast improved stochastic expectation-maximization (iStEM) algorithm suitable for large-scale data; FCGDINA also provides a deterministic expectation-maximization (EM) estimator. Comprehensive model evaluation uses the limited-information M2 family of goodness-of-fit statistics (Maydeu-Olivares and Joe, 2005 <doi:10.1198/016214504000002069>; 2006 <doi:10.1007/s11336-005-1295-9>) together with root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker-Lewis index (TLI), and standardized root mean square residual (SRMSR).

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: coda, GPArotation, MASS, methods, numDeriv, parallel, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), rstantools (≥ 2.6.0)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppArmadillo, RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests: knitr, loo, rmarkdown
Published: 2026-07-30
DOI: 10.32614/CRAN.package.ForceChoice (may not be active yet)
Author: Haijiang Qin ORCID iD [aut, cre, cph], Lei Guo ORCID iD [aut, cph]
Maintainer: Haijiang Qin <haijiang133 at outlook.com>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README, NEWS
CRAN checks: ForceChoice results

Documentation:

Reference manual: ForceChoice.html , ForceChoice.pdf
Vignettes: Introduction to ForceChoice (source, R code)
Model Theory and Selection Guide (source, R code)

Downloads:

Package source: ForceChoice_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): ForceChoice_1.0.0.tgz, r-oldrel (arm64): ForceChoice_1.0.0.tgz, r-release (x86_64): ForceChoice_1.0.0.tgz, r-oldrel (x86_64): ForceChoice_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ForceChoice to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.