mixedsubjectsirt: Item Response Theory Calibration with a Mixed Subjects Design

Integrates large language model generated item responses into psychometric calibration studies through a mixed-subjects design for unidimensional two-parameter and one-parameter logistic item response theory models. Human pilot responses are augmented with model-generated responses using a prediction-powered inference estimator (Angelopoulos, Bates, Fannjiang, Jordan and Zrnic (2023) <doi:10.1126/science.adi6000>; Angelopoulos, Duchi and Zrnic (2023) <doi:10.48550/arXiv.2311.01453>) adapted to marginal maximum-likelihood estimation, following the mixed-subjects design of Broska, Howes and van Loon (2025) <doi:10.1177/00491241251326865>. The estimator is anchored to the human responses and is asymptotically unbiased for the human item parameters at any tuning weight; the weight on the synthetic responses is chosen to minimize propagated ability-score risk, down-weighting uninformative or biased generated responses. Louis-corrected sandwich standard errors, ability scoring, cross-fitted tuning, and scale linking are also provided.

Version:	1.0.0
Imports:	mirt, rmutil
Suggests:	ggplot2, knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-06-25
DOI:	10.32614/CRAN.package.mixedsubjectsirt (may not be active yet)
Author:	Klint Kanopka [aut, cre]
Maintainer:	Klint Kanopka <klint.kanopka at nyu.edu>
BugReports:	https://github.com/klintkanopka/mixedsubjectsirt/issues
License:	MIT + file LICENSE
URL:	https://klintkanopka.com/mixedsubjectsirt/, https://github.com/klintkanopka/mixedsubjectsirt
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	mixedsubjectsirt results

Documentation:

Reference manual:

mixedsubjectsirt.html , mixedsubjectsirt.pdf

Vignettes:

Per-Item Lambda (Experimental) (source, R code) Choosing Lambda in Mixed-Subjects IRT (source, R code) IRT Linking and Gradient Asymmetry: Diagnostic Guide (source, R code) Mixed-Subjects 1PL Calibration (source, R code) Mixed-Subjects IRT Calibration (source, R code) Simulation Validation of the Mixed-Subjects MML Estimator (source, R code) Understanding Ability-Risk Tuning (source, R code) Calibrating with a Weakly-Informative, Biased LLM (source, R code)

Downloads:

Package source:	mixedsubjectsirt_1.0.0.tar.gz
Windows binaries:	r-devel: mixedsubjectsirt_1.0.0.zip, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): mixedsubjectsirt_1.0.0.tgz, r-oldrel (arm64): mixedsubjectsirt_1.0.0.tgz, r-release (x86_64): mixedsubjectsirt_1.0.0.tgz, r-oldrel (x86_64): mixedsubjectsirt_1.0.0.tgz

Linking:

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