Item Response Theory Analysis Made Simple
Transform complex psychometric analysis into actionable insights. Build IRT models, analyze item parameters, and evaluate test performance with AI assistance.
Item Response Theory (IRT) doesn't have to be intimidating. While traditional IRT analysis requires mastering complex statistical software and writing lengthy code, Sourcetable transforms this process into something intuitive and accessible.
Whether you're developing psychological assessments, analyzing educational test data, or evaluating survey instruments, our AI-powered platform handles the heavy lifting while you focus on interpreting results and making decisions.
Why Choose Sourcetable for IRT Analysis?
No Coding Required
Build 1PL, 2PL, 3PL, and Rasch models without writing a single line of R or Python code. Simply describe your analysis needs in plain English.
Instant Model Diagnostics
Get comprehensive model fit statistics, item characteristic curves, and test information functions generated automatically with AI assistance.
Visual Insights
Create publication-ready charts including ICCs, TIFs, and person-item maps with just a few clicks. Perfect for research presentations and reports.
Real-time Collaboration
Share your IRT models and results with colleagues instantly. Make revisions together and maintain version control effortlessly.
Excel Integration
Import your existing test data from Excel or CSV files. Export results back to familiar formats for further analysis or reporting.
Automated Reporting
Generate comprehensive IRT analysis reports including item parameters, person abilities, and model comparisons automatically.
From Data to Insights in Four Steps
See how Sourcetable streamlines your IRT analysis workflow
Upload Your Test Data
Import response data from Excel, CSV, or paste directly. Include item responses, person IDs, and any demographic variables you need for analysis.
Specify Your Model
Tell our AI what type of IRT model you want to fit. Choose from Rasch, 1PL, 2PL, 3PL, or graded response models using natural language.
Review Results
Examine item parameters, person abilities, and model fit statistics. Generate item characteristic curves and test information functions instantly.
Create Reports
Export professional reports with tables, charts, and interpretations. Share findings with stakeholders or include in research publications.
Real-World IRT Applications
Discover how psychology professionals use Sourcetable for Item Response Theory analysis
Personality Assessment Development
A clinical psychology team developed a new anxiety screening tool using IRT analysis to optimize item selection and establish cut-off scores. They identified items with poor discrimination and refined their instrument to achieve better measurement precision.
Educational Testing Programs
A university testing center uses IRT models to analyze exam performance across different student populations. They identify biased items, establish equivalent test forms, and provide detailed feedback to faculty about item quality.
Clinical Outcome Measures
A research hospital analyzes patient-reported outcome measures using graded response models. They track treatment effectiveness over time and identify which items best differentiate between severity levels.
Survey Research Validation
A market research firm validates attitude scales using IRT analysis to ensure their surveys provide reliable measurements across diverse demographic groups. They optimize questionnaire length while maintaining measurement quality.
Computerized Adaptive Testing
An online learning platform implements adaptive testing using IRT item banks. They provide personalized assessments that adjust difficulty based on student ability, reducing test time while maintaining accuracy.
Cross-Cultural Validation
International researchers use differential item functioning analysis to validate psychological measures across cultures. They identify items that perform differently between groups and ensure fair assessment practices.
Step-by-Step IRT Analysis Examples
Example 1: Depression Screening Scale Analysis
Let's analyze a 10-item depression screening questionnaire using a 2-parameter logistic model. Your data includes binary responses (0/1) from 500 participants.
Step 1: Upload your response matrix with participant IDs in column A and item responses in columns B through K.
Step 2: Ask Sourcetable: "Fit a 2PL IRT model to items B1:K500 and show me the item parameters with 95% confidence intervals."
Step 3: Review the discrimination (a) and difficulty (b) parameters. Items with low discrimination (a < 0.5) may need revision.
Step 4: Generate item characteristic curves to visualize how each item performs across the ability spectrum.
Example 2: Comparing Test Forms
You have two versions of a cognitive ability test and want to establish if they're equivalent for score reporting.
Analysis approach: Use anchor items present in both forms to link the scales, then compare test information functions to ensure equivalent measurement precision.
Simply tell Sourcetable: "Perform IRT linking analysis between Form A (columns B:M) and Form B (columns N:Y) using items 1, 5, and 9 as anchors."
Example 3: Identifying Problematic Items
During test development, you need to identify items that don't fit the IRT model assumptions.
Diagnostic steps: Examine item fit statistics, look for items with negative discrimination, check for local independence violations, and review differential item functioning across groups.
Ask Sourcetable: "Calculate item fit statistics and flag any items with poor model fit. Also check for DIF by gender using the Mantel-Haenszel procedure."
Advanced IRT Capabilities
Multidimensional IRT
Analyze tests measuring multiple latent traits simultaneously. Perfect for complex psychological constructs with multiple facets.
Differential Item Functioning
Detect item bias across demographic groups using statistical and graphical methods. Ensure fair assessment practices.
Graded Response Models
Handle polytomous items like Likert scales with appropriate IRT models. Analyze ordered categorical responses accurately.
Test Linking & Equating
Link multiple test forms or track ability changes over time using common person or common item designs.
Frequently Asked Questions
What types of IRT models does Sourcetable support?
Sourcetable supports all major IRT models including Rasch (1PL), 2-parameter logistic (2PL), 3-parameter logistic (3PL), graded response models for polytomous items, and multidimensional IRT models. You can specify your preferred model using natural language.
Can I import data from SPSS or other statistical software?
Yes, you can import data from any format including SPSS (.sav), Excel (.xlsx), CSV, and tab-delimited files. Sourcetable automatically detects your data structure and prepares it for IRT analysis.
How does Sourcetable handle missing data in IRT analysis?
Sourcetable uses modern missing data techniques including full information maximum likelihood (FIML) estimation, which provides more accurate parameter estimates than traditional methods like listwise deletion.
Can I perform differential item functioning (DIF) analysis?
Absolutely. Sourcetable includes comprehensive DIF detection using multiple methods including Mantel-Haenszel, logistic regression, and IRT-based approaches. You can test for uniform and non-uniform DIF across any grouping variable.
What sample size do I need for reliable IRT analysis?
Sample size requirements depend on your model complexity and precision needs. Generally, 200+ participants work well for simple models, while complex multidimensional models may require 500+ participants. Sourcetable provides guidance based on your specific analysis.
Can I create publication-ready visualizations?
Yes, Sourcetable generates high-quality charts including item characteristic curves, test information functions, person-item maps, and Wright maps. All visualizations are publication-ready and can be customized for your needs.
How do I interpret IRT parameter estimates?
Sourcetable provides plain-English interpretations alongside technical results. For example, it explains that higher discrimination parameters indicate items that better differentiate between ability levels, making complex psychometric concepts accessible.
Can I compare multiple IRT models?
Yes, you can fit multiple models and compare them using information criteria (AIC, BIC), likelihood ratio tests, and practical fit indices. Sourcetable helps you choose the best model for your data and research goals.
Sourcetable Frequently Asked Questions
How do I analyze data?
To analyze spreadsheet data, just upload a file and start asking questions. Sourcetable's AI can answer questions and do work for you. You can also take manual control, leveraging all the formulas and features you expect from Excel, Google Sheets or Python.
What data sources are supported?
We currently support a variety of data file formats including spreadsheets (.xls, .xlsx, .csv), tabular data (.tsv), JSON, and database data (MySQL, PostgreSQL, MongoDB). We also support application data, and most plain text data.
What data science tools are available?
Sourcetable's AI analyzes and cleans data without you having to write code. Use Python, SQL, NumPy, Pandas, SciPy, Scikit-learn, StatsModels, Matplotlib, Plotly, and Seaborn.
Can I analyze spreadsheets with multiple tabs?
Yes! Sourcetable's AI makes intelligent decisions on what spreadsheet data is being referred to in the chat. This is helpful for tasks like cross-tab VLOOKUPs. If you prefer more control, you can also refer to specific tabs by name.
Can I generate data visualizations?
Yes! It's very easy to generate clean-looking data visualizations using Sourcetable. Simply prompt the AI to create a chart or graph. All visualizations are downloadable and can be exported as interactive embeds.
What is the maximum file size?
Sourcetable supports files up to 10GB in size. Larger file limits are available upon request. For best AI performance on large datasets, make use of pivots and summaries.
Is this free?
Yes! Sourcetable's spreadsheet is free to use, just like Google Sheets. AI features have a daily usage limit. Users can upgrade to the pro plan for more credits.
Is there a discount for students, professors, or teachers?
Currently, Sourcetable is free for students and faculty, courtesy of free credits from OpenAI and Anthropic. Once those are exhausted, we will skip to a 50% discount plan.
Is Sourcetable programmable?
Yes. Regular spreadsheet users have full A1 formula-style referencing at their disposal. Advanced users can make use of Sourcetable's SQL editor and GUI, or ask our AI to write code for you.
Transform Your Psychometric Analysis Today
Join thousands of psychology professionals using Sourcetable to streamline their Item Response Theory analysis workflow.