Helper functions and example data sets to facilitate the estimation of IRTree models from data with different shape and using different software.

Estimation of reliability coefficients for ability estimates and sum scores from item response theory models as defined in Cheng, Y., Yuan, K.-H. and Liu, C. (2012) <doi:10.1177/0013164411407315> and Kim, S. and Feldt, L. S. (2010) <doi:10.1007/s12564-009-9062-8>. The package supports the 3-PL and generalized partial credit models and includes estimates of the standard errors of the reliability coefficient estimators, derived in Andersson, B. and Xin, T. (2018) <doi:10.1177/0013164417713570>.

Interactive shiny application for running Item Response Theory
    analysis. Provides graphics for characteristic and information curves.

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), three-parameter logistic (3PL), graded response (GRM),
    partial credit (PCM), and generalized partial credit (GPCM) 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.

The ISA is a biclustering algorithm that finds modules 
  in an input matrix. A module or bicluster is a block of the
  reordered input matrix.

We provide data sets used in the textbook "Introduction to Sports Analytics using R" by Elmore and Urbaczweski (2025).

These are data and functions to support quantitative peace science
    research. The data are important state-year information on democracy and
    wealth, which require periodic updates and regular maintenance. The
    functions permit some exploratory and diagnostic assessment of the kinds of
    data in demand by the community, but do not impose many dependencies on the
    user.