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irtsim  

Monte Carlo Simulation-Based Sample-Size Planning for Item Response Theory
View on CRAN: Click here


Download and install irtsim package within the R console
Install from CRAN:
install.packages("irtsim")

Install from Github:
library("remotes")
install_github("cran/irtsim")

Install by package version:
library("remotes")
install_version("irtsim", "0.1.1")



Attach the package and use:
library("irtsim")
Maintained by
Stephen Ward
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-23
Latest Update: 2026-04-23
Description:
Provides a pipeline application programming interface (API) for Monte Carlo simulation-based sample-size planning in item response theory (IRT). Implements the 10-decision framework from Schroeders and Gnambs (2025) <doi:10.1177/25152459251314798> as a three-step workflow: specify the data-generating model with irt_design(), add study conditions with irt_study(), and run simulations with irt_simulate(). Supports one-parameter logistic (1PL), two-parameter logistic (2PL), and graded response models with missing-completely-at-random (MCAR), missing-at-random (MAR), booklet, and linking missingness mechanisms. Results include mean squared error (MSE), bias, root mean squared error (RMSE), standard error (SE), and coverage criteria with summary and plot methods.
How to cite:
Stephen Ward (2026). irtsim: Monte Carlo Simulation-Based Sample-Size Planning for Item Response Theory. R package version 0.1.1, https://cran.r-project.org/web/packages/irtsim. Accessed 29 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:50), 0.1.1 (2026-04-23 21:50), 0.1.2 (2026-05-05 13:40)
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Complete documentation for irtsim
Functions, R codes and Examples using the irtsim R package
Full irtsim package functions and examples
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