Coefficient alpha: a useful indicator of reliability?

Mark Shevlin, JNV Miles, MNO Davies, S Walker

Research output: Contribution to journalArticle

86 Citations (Scopus)

Abstract

A series of Monte Carlo simulations were carried out to examine the performance of Cronbach's alpha as an index of reliability. Data were generated to be consistent with a single factor measured with six items. The magnitude of the factor loadings, systematic error and sample size were manipulated and alpha calculated from random samples. The results showed that alpha is influenced by factors other than the reliability of the items that comprise a scale. In particular the amount of systematic error, or deviation from unidimensionality, increased the estimate of alpha. The results are discussed in terms of traditional interpretation of alpha. (C) 1999 Elsevier Science Ltd. All rights reserved.
LanguageEnglish
Pages229-237
JournalPersonality and Individual Differences
Volume28
Issue number2
Publication statusPublished - Feb 2000

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Shevlin, M., Miles, JNV., Davies, MNO., & Walker, S. (2000). Coefficient alpha: a useful indicator of reliability? Personality and Individual Differences, 28(2), 229-237.
Shevlin, Mark ; Miles, JNV ; Davies, MNO ; Walker, S. / Coefficient alpha: a useful indicator of reliability?. In: Personality and Individual Differences. 2000 ; Vol. 28, No. 2. pp. 229-237.
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Shevlin, M, Miles, JNV, Davies, MNO & Walker, S 2000, 'Coefficient alpha: a useful indicator of reliability?', Personality and Individual Differences, vol. 28, no. 2, pp. 229-237.

Coefficient alpha: a useful indicator of reliability? / Shevlin, Mark; Miles, JNV; Davies, MNO; Walker, S.

In: Personality and Individual Differences, Vol. 28, No. 2, 02.2000, p. 229-237.

Research output: Contribution to journalArticle

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AU - Davies, MNO

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AB - A series of Monte Carlo simulations were carried out to examine the performance of Cronbach's alpha as an index of reliability. Data were generated to be consistent with a single factor measured with six items. The magnitude of the factor loadings, systematic error and sample size were manipulated and alpha calculated from random samples. The results showed that alpha is influenced by factors other than the reliability of the items that comprise a scale. In particular the amount of systematic error, or deviation from unidimensionality, increased the estimate of alpha. The results are discussed in terms of traditional interpretation of alpha. (C) 1999 Elsevier Science Ltd. All rights reserved.

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