IRTify is a powerful tool for analyzing test data, providing comprehensive insights into Item Response Theory (IRT) and Differential Item Functioning (DIF). Built using Streamlit in Python, this app leverages R for conducting detailed statistical analyses, allowing educators, researchers, and psychometricians to effortlessly explore and interpret test performance data, ensuring a deeper understanding of test reliability and validity.
- Item Response Theory Analysis: Gain detailed insights into item characteristics and examine test-taker abilities using various IRT models.
- Differential Item Functioning: Identify items that function differently across diverse groups of test-takers, ensuring fairness and equity in testing.
- User-Friendly Interface: Intuitive and interactive Streamlit interface for easy navigation and analysis.
- Visualizations: Generate and export various plots to visualize IRT parameters and DIF results.
- Data Import/Export: Seamlessly import test data and export analysis results for further use.
- R Integration: Advanced statistical analyses are performed using R, ensuring robust and accurate results.
To get started with IRTify, follow the instructions in the repository to set up your environment and run the app locally.
Contributions are welcome! If you'd like to improve IRTify, please fork the repository and submit a pull request.
This project is licensed under the MIT License.