irtsim-package: irtsim: Monte Carlo Simulation-Based Sample-Size Planning for...

In irtsim: Monte Carlo Simulation-Based Sample-Size Planning for Item Response Theory

irtsim: Monte Carlo Simulation-Based Sample-Size Planning for Item Response Theory

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) \Sexpr[results=rd]{tools:::Rd_expr_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.

Author(s)

Maintainer: Stephen Ward [e-mail]

See Also

Useful links:

• https://github.com/sward1/irtsim

• Report bugs at https://github.com/sward1/irtsim/issues

irtsim documentation built on April 24, 2026, 1:07 a.m.