Introduction to measureR
Introduction to measureR
Overview
measureR provides a unified Shiny-based environment for
educational and psychological measurement,
including:
- Content Validity (CV)
- Exploratory Factor Analysis (EFA)
- Confirmatory Factor Analysis (CFA)
- Classical Test Theory (CTT)
- Item Response Theory (IRT)
The package is designed for users who prefer a graphical workflow
without writing code, while still leveraging robust statistical
methodologies implemented in well-established R packages.
Installation
install.packages("measureR")
library(measureR)
Launching the Application
library(measureR)
run_measureR()
This will open the full Shiny interface, where you can upload data,
choose an analysis module, and generate results.
Modules Included
✔ Content Validity (CV)
- Aiken’s V, CVR (Lawshe), I-CVI, and S-CVI/Ave computation.
- Automatic critical value comparison and interpretation badges.
- Clear tabular summaries and export-ready results.
✔ Exploratory Factor Analysis (EFA)
- KMO, Bartlett test, parallel analysis.
- Factor extraction with rotation.
- Factor scores and loading matrix export.
- Clean HTML summaries for clearer interpretation.
✔ Confirmatory Factor Analysis (CFA)
- Lavaan model editor.
- Fit measures, loadings, factor scores.
- Fully customized SEM path diagrams.
✔ Classical Test Theory (CTT)
- Item difficulty and discrimination indices.
- Test reliability (α), SEM, and score distribution analysis.
- Distractor analysis for multiple-choice items.
- Comprehensive item and test-level summary outputs.
✔ Item Response Theory (IRT)
- Supports dichotomous and polytomous items.
- Automatically fits Rasch, 2PL, 3PL (or PCM/GRM/GPCM).
- ICC plots, test information, factor scores.
Multi-dimensional
visualization with 3D surfaces and heatmaps.
Once inside the GUI:
- Choose a module (e.g., IRT)
- Upload your dataset or select a built-in dataset
- Choose variables and model settings
- Fit the models and explore the outputs
Reproducibility and Reporting
measureR provides:
- Exportable tables (CSV, Excel)
- Downloadable graphics (PNG)
- Reproducible summaries and model comparisons
This ensures results produced through the GUI can be published or
documented with confidence.