Reliability & Validity Checker
Ensure your research instruments meet rigorous psychometric standards with this advanced reliability and validity analysis tool. Whether you're developing surveys, validating scales, or analyzing test data, this tool provides comprehensive metrics including Cronbach's Alpha, Split-Half reliability, Test-Retest correlations, and Inter-Rater reliability (ICC). Perfect for researchers, psychologists, educators, and data scientists who need to validate measurement instruments and ensure data quality. Features interactive visualizations, detailed interpretations, and export capabilities for publication-ready results.
Key Features
- Cronbach's Alpha calculation with 95% confidence intervals for internal consistency
- Split-Half reliability using Spearman-Brown correction formula
- Test-Retest reliability analysis for temporal stability assessment
- Inter-Rater reliability (ICC) for multiple rater agreement analysis
- Content Validity Index (CVI) and Content Validity Ratio (CVR) calculations
- Construct validity assessment with convergent and discriminant validity metrics
- Criterion validity analysis with concurrent and predictive validity measures
- Comprehensive data quality analysis with completeness and consistency scoring
- Statistical power analysis and sample size recommendations
- Interactive visualizations including bar charts and radar plots
- Automated interpretation with professional recommendations
- Support for scale/survey, test-retest, and inter-rater data formats
- CSV and JSON data import with example data generation
- Export results in JSON format for further analysis
- Built-in interpretation guidelines based on established psychometric standards
- Outlier detection using z-score methodology
- Standard error and confidence interval calculations
Share This Tool
This tool is 100% free and requires no login
Loading tool...
This may take a few seconds
Frequently Asked Questions
What is Cronbach's alpha and what value is considered good?
Cronbach's alpha (α) measures internal consistency reliability - how closely related a set of items are as a group. Values range from 0 to 1. Generally, α ≥ 0.70 is acceptable, α ≥ 0.80 is good, and α ≥ 0.90 is excellent for research purposes. Values above 0.95 may indicate redundancy. This tool calculates Cronbach's alpha and provides interpretation based on established psychometric standards.
What is the difference between reliability and validity?
Reliability measures consistency (does your instrument produce stable results over time or across items?), while validity measures accuracy (does it actually measure what it claims to measure?). An instrument can be reliable without being valid, but cannot be valid without being reliable. This tool assesses both: reliability through Cronbach's α, split-half, and test-retest methods, and validity through content validity index (CVI) and correlation analyses.
What types of reliability can this tool calculate?
The tool calculates four types of reliability: (1) Internal consistency using Cronbach's alpha and split-half reliability, (2) Test-retest reliability for stability over time, (3) Inter-rater reliability using Intraclass Correlation Coefficient (ICC) for agreement between raters, and (4) Item-total correlations to identify problematic items. Each comes with statistical interpretation and recommendations.
How many items do I need for reliability analysis?
Minimum 3 items for Cronbach's alpha, though 5-10 items is ideal for stable estimates. For test-retest reliability, you need data from the same participants at two time points. For inter-rater reliability, you need ratings from 2+ raters on the same subjects. Sample size should be at least 100-300 participants for stable reliability estimates, though smaller samples (30-50) can provide preliminary estimates.