Department of Methodology and Statistics, Utrecht University.
Psychol Methods. 2018 Sep;23(3):412-433. doi: 10.1037/met0000144. Epub 2017 May 29.
Empirical studies in psychology commonly report Cronbach's alpha as a measure of internal consistency reliability despite the fact that many methodological studies have shown that Cronbach's alpha is riddled with problems stemming from unrealistic assumptions. In many circumstances, violating these assumptions yields estimates of reliability that are too small, making measures look less reliable than they actually are. Although methodological critiques of Cronbach's alpha are being cited with increasing frequency in empirical studies, in this tutorial we discuss how the trend is not necessarily improving methodology used in the literature. That is, many studies continue to use Cronbach's alpha without regard for its assumptions or merely cite methodological articles advising against its use to rationalize unfavorable Cronbach's alpha estimates. This tutorial first provides evidence that recommendations against Cronbach's alpha have not appreciably changed how empirical studies report reliability. Then, we summarize the drawbacks of Cronbach's alpha conceptually without relying on mathematical or simulation-based arguments so that these arguments are accessible to a broad audience. We continue by discussing several alternative measures that make less rigid assumptions which provide justifiably higher estimates of reliability compared to Cronbach's alpha. We conclude with empirical examples to illustrate advantages of alternative measures of reliability including omega total, Revelle's omega total, the greatest lower bound, and Coefficient H. A detailed software appendix is also provided to help researchers implement alternative methods. (PsycINFO Database Record
心理学的实证研究通常报告 Cronbach's alpha 作为内部一致性可靠性的度量，尽管许多方法学研究表明 Cronbach's alpha 存在许多问题，这些问题源于不切实际的假设。在许多情况下，违反这些假设会导致可靠性估计值过小，从而使测量看起来不如实际可靠。尽管方法学对 Cronbach's alpha 的批评在实证研究中被越来越频繁地引用，但在本教程中，我们讨论了这种趋势并不一定能改善文献中使用的方法。也就是说，许多研究继续使用 Cronbach's alpha，而不考虑其假设，或者仅仅引用方法学文章，以合理化不利的 Cronbach's alpha 估计值。本教程首先提供证据表明，反对 Cronbach's alpha 的建议并没有显著改变实证研究报告可靠性的方式。然后，我们从概念上总结了 Cronbach's alpha 的缺点，而不依赖于数学或基于模拟的论证，以便这些论证能够为更广泛的受众所理解。我们接着讨论了几种替代措施，这些措施的假设更为灵活，与 Cronbach's alpha 相比，提供了更合理的可靠性估计值。最后，我们通过实证示例来说明替代可靠性测量方法的优势，包括 omega 总、Revelle 的 omega 总、最大下限和 H 系数。还提供了详细的软件附录，以帮助研究人员实施替代方法。
