Cronbach’s Coefficient Alpha: Well Known but Poorly Understood

This study disproves the following six common misconceptions about coefficient alpha: (a) Alpha was first developed by Cronbach. (b) Alpha equals reliability. (c) A high value of alpha is an indication of internal consistency. (d) Reliability will always be improved by deleting items using “alpha if...

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Bibliographic Details
Published in:Organizational research methods 2015-04, Vol.18 (2), p.207-230
Main Authors: Cho, Eunseong, Kim, Seonghoon
Format: Article
Language:English
Subjects:
Coefficients
Computation
Consistency
Estimates
Estimating techniques
Estimators
Indication
Mathematical analysis
Mathematical models
Quantitative psychology
Reliability
Research methodology
Statistical methods
Studies
Citations: Items that this one cites
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Summary:This study disproves the following six common misconceptions about coefficient alpha: (a) Alpha was first developed by Cronbach. (b) Alpha equals reliability. (c) A high value of alpha is an indication of internal consistency. (d) Reliability will always be improved by deleting items using “alpha if item deleted.” (e) Alpha should be greater than or equal to .7 (or, alternatively, .8). (f) Alpha is the best choice among all published reliability coefficients. This study discusses the inaccuracy of each of these misconceptions and provides a correct statement. This study recommends that the assumptions of unidimensionality and tau-equivalency be examined before the application of alpha and that structural equation modeling (SEM)–based reliability estimators be substituted for alpha when one of these conditions is not satisfied. This study also provides formulas for SEM-based reliability estimators that do not rely on matrix notation and step-by-step explanations for the computation of SEM-based reliability estimates.
ISSN:1094-4281
1552-7425
DOI:10.1177/1094428114555994