Description
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) <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.