Volume 36, Issue 1
Researcher's Notebook

Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning

Douglas G. Bonett

Corresponding Author

Psychology Department, University of California, Santa Cruz, California, U.S.A.

Correspondence to: Douglas G. Bonett, Psychology Department, University of California, Santa Cruz, California 95064, U.S.A. E‐mail: dgbonett@ucsc.eduSearch for more papers by this author
Thomas A. Wright

Gabelli School of Business, Fordham University, Bronx, New York, U.S.A.

Search for more papers by this author
First published: 13 October 2014
Citations: 105

Summary

Cronbach's alpha is one of the most widely used measures of reliability in the social and organizational sciences. Current practice is to report the sample value of Cronbach's alpha reliability, but a confidence interval for the population reliability value also should be reported. The traditional confidence interval for the population value of Cronbach's alpha makes an unnecessarily restrictive assumption that the multiple measurements have equal variances and equal covariances. We propose a confidence interval that does not require equal variances or equal covariances. The results of a simulation study demonstrated that the proposed method performed better than alternative methods. We also present some sample size formulas that approximate the sample size requirements for desired power or desired confidence interval precision. R functions are provided that can be used to implement the proposed confidence interval and sample size methods. Copyright © 2014 John Wiley & Sons, Ltd.

Number of times cited according to CrossRef: 105

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