Cronbach's alpha is a statistic for investigating the internal consistency of a questionnaire (Cronbach, 1951; Bland & Altman, 1997).
Each question of the questionnaire results in one variable and the answers (numerically coded) are entered in the respective columns of the data table. The answers of one subject are entered on one row of the data table.
- Variables: the variables that contain the answers to the different questions of the questionnaire.
- Filter: an optional filter to include only a selected subgroup of subjects (rows).
- Correct for scale reversal: Some variables may be inversely related to other variables. When you select the option "Correct for scale reversal", SciStat.com will detect these variables automatically (based on the correlation matrix) and reverse the values of those variables before analysis.
SciStat.com reports Cronbach's alpha with its lower confidence limit (Feldt, 1965).
Next, SciStat.com calculates the alpha obtained with each question in turn dropped. If the deletion of a question causes a considerable increase in alpha then you should consider dropping that question from the questionnaire.
SciStat.com calculates Cronbach's alpha using the raw data and on the standardized variables (a transformation so that their mean is 0 and variance is 1). Using the "raw" data, questions that have more variability contribute more to the variability of the resulting scale; in the "standardized" form, each question gets equal weight.
For research purposes alpha should be more than 0.7 to 0.8, but for clinical purposes alpha should at least be 0.90 (Bland & Altman, 1997).
- Cronbach LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16:297-334.
- Bland JM, Altman DG (1997) Statistics notes: Cronbach's alpha. British Medical Journal 314:572.
- Feldt LS (1965) The approximate sampling distribution of Kuder-Richardson reliability coefficient twenty. Psychometrika 30:357-371.
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