The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation
Abstract
Coefficient alpha is the most popular measure of reliability (and certainly of internal consistency reliability) reported in psychological research. This is noteworthy given the numerous deficiencies of coefficient alpha documented in the psychometric literature. This mismatch between theory and practice appears to arise partly because users of psychological scales are unfamiliar with the psychometric literature on coefficient alpha and partly because alternatives to alpha are not widely known. We present a brief review of the psychometric literature on coefficient alpha, followed by a practical alternative in the form of coefficient omega. To facilitate the shift from alpha to omega, we also present a brief guide to the calculation of point and interval estimates of omega using a free, open source software environment.
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Citations
Cites
Coefficient Alpha and the Internal Structure of Tests
Cronbach, L. J. (1951) · Psychometrika · doi:10.1007/bf02310555 · Cited by 43,931
What is coefficient alpha? An examination of theory and applications
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“Other authors have shown that estimation of reliability of alpha can also be inflated when the errors for each item are correlated or the number of items is significantly increased (Cortina, 1993; Yuan & Bentler, 2002).”
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Cited by
Use Omega Rather than Cronbach’s Alpha for Estimating Reliability. But…
Hayes, A. F., & Coutts, J. J. (2020) · Communication Methods and Measures · doi:10.1080/19312458.2020.1718629 · Cited by 2,675
Thanks coefficient alpha, we’ll take it from here.
McNeish, D. (2018) · Psychological Methods · doi:10.1037/met0000144 · Cited by 2,533
Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024) · Asia Pacific Journal of Management · doi:10.1007/s10490-023-09871-y · Cited by 2,262
“Similar to other researchers (e.g., Dunn et al., 2014; Kelley & Cheng, 2012; Kelley & Pornprasertmanit, 2016; Raykov, 2002), we recommend generating CIs by bootstrapping because the estimated quality measures may not be normally distributed.”
Evaluating Bifactor Models: Calculating and Interpreting Statistical Indices
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016) · Psychological Methods · doi:10.1037/met0000045 · Cited by 1,599
O’Brien, H. L., Cairns, P., & Hall, M. (2018) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2018.01.004 · Cited by 1,014
Metadata
- Authors
- Dunn, T. J., Baguley, T., & Brunsden, V.
- Venue
- British Journal of Psychology
- Publisher
- Wiley
- Published
- 2013-08-06
- Volume
- 105
- Issue
- 3
- Pages
- 399-412
- ISSN
- 0007-1269 (ISSN-L)
- 2044-8295
- OpenAlex
- W2075004202
- Cited by
- 3,596
- References
- 8
- FWCI
- 65.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Funders
- Economic and Social Research Council
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