Cronbach Alpha Calculator
Cronbach alpha online with item-total correlations, alpha if item deleted and 95 percent CI.
When to use it
Use to estimate the internal consistency of a multi-item scale (Likert questionnaire, attitude inventory, behavioural rating). Reported in nearly every psychometric and survey-based paper. Pair with item-total correlations and an alpha-if-deleted scan to identify weak items.
When NOT to use it
Do not use as the only reliability measure; alpha assumes essentially tau-equivalent items. For congeneric items use McDonald's omega instead. Do not use when items are scored on different metrics without standardising. Do not use to argue a scale is uni-dimensional; that requires factor analysis.
What you get
Cronbach's alpha for the full scale with its 95 percent confidence interval (Feldt formula); alpha-if-item-deleted for each item; item-total correlations (corrected); item statistics (mean, SD); the inter-item correlation matrix.
How to interpret the output
Conventional thresholds: alpha at or above 0.7 is acceptable for research instruments; 0.8 plus is good; 0.9 plus is excellent (Nunnally and Bernstein 1994). Alpha above 0.95 may indicate redundancy. An alpha-if-deleted that is much higher than the overall alpha flags a problematic item to drop. Item-total correlation below 0.3 suggests the item does not measure the same construct.
Common pitfalls
- Reporting alpha as if it implied uni-dimensionality.
- Inflating alpha by adding redundant items.
- Not reverse-coding negatively-worded items before computing alpha.
- Using alpha for a scale of 3 or fewer items (unstable).
Try it in StatVeda
The Cronbach's alpha (reliability) engine runs entirely in the browser. No signup, no install, no data sent to a server. Paste your data, hit Run, copy the output.
Open Cronbach's alpha (reliability)References
- Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297 to 334.
- Nunnally, J. C. and Bernstein, I. H. (1994). Psychometric Theory, 3rd edition. McGraw-Hill, New York.
- Feldt, L. S., Woodruff, D. J. and Salih, F. A. (1987). Statistical inference for coefficient alpha. Applied Psychological Measurement, 11(1), 93 to 103.