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sspLNIRT

Lifecycle: experimental R-CMD-check Codecov test coverage

sspLNIRT is a sample size planning tool for item calibration with the Joint Hierarchical Model (JHM) of response accuracy and response time. It estimates the minimum sample size required to achieve a target accuracy (RMSE) of item parameter estimates under a specified data-generating process.

The package provides:

  • Precomputed results for various design conditions, accessible instantly via a Shiny app and/or R package.
  • Custom Sample Size Estimation via optim_sample() for design conditions outside the precomputed data.
  • Diagnostic functions for inspecting parameter accuracy or bias, power curves, and implied response time and response accuracy distributions.

Usage

The tool is available as an R package and as an interactive Shiny app.

Web App

Use the app at sebastian-lortz.shinyapps.io/sspLNIRT.

Installation

You can install the latest version of the R package from GitHub:

# install devtools if needed
if (!requireNamespace("devtools")) {install.packages("devtools")}

# install from GitHub
devtools::install_github("sebastian-lortz/sspLNIRT")

System Requirements

The sspLNIRT package was built under R version 4.4.3 using Apple clang version 16.0.0 (clang-1600.0.26.6) and GNU Fortran (GCC) 14.2.0. To compile R packages from source, install the appropriate toolchain:

Run

Launch the Shiny app locally with:

sspLNIRT::run_app()

Documentation

Vignettes and full function documentation are available at sebastian-lortz.github.io/sspLNIRT.

Citation

Please cite sspLNIRT if you use it. To cite the software, use:

Lortz S (2026). sspLNIRT: Sample Size Planning for Item Calibration using the Joint Hierarchical Model. R package version 0.0.0.9000, https://github.com/sebastian-lortz/sspLNIRT.

Or copy the reference information to your BibTeX file:

@Manual{,
    title = {sspLNIRT: Sample Size Planning for Item Calibration using the Joint Hierarchical Model},
    author = {Sebastian A. J. Lortz},
    year = {2026},
    note = {R package version 0.0.0.9000},
    url = {https://github.com/sebastian-lortz/sspLNIRT},
  }

Code of Conduct

I am open to feedback and new ideas. Please mind the Contributor Code of Conduct.

About

You are reading the doc about version: 0.0.0.9000

This README has been compiled on 2026-05-10 23:13:30.

About

Sample size planning tools for the Joint Hierarchical Model using a 2-PL normal ogive model for response accuracy and a 3-PL log-normal model for response time. Precomputed results can be accessed instantly, custom designs can be computed, and diagnostics can be used to interpret results.

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LICENSE.md

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