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Psychometrics and the Measurement of Emotional Intelligence

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Book cover Assessing Emotional Intelligence

Part of the book series: The Springer Series on Human Exceptionality ((SSHE))

It may be suggested that the measurement of emotional intelligence (EI) has been met with a non-negligible amount of scepticism and criticism within academia, with some commentators suggesting that the area has suffered from a general lack of psychometric and statistical rigour (Brody, 2004). To potentially help ameliorate this noted lack of sophistication, as well as to facilitate an understanding of many of the research strategies and findings reported in the various chapters of this book, this chapter will describe and elucidate several of the primary psychometric considerations in the evaluation of an inventory or test purported to measure a particular attribute or construct. To this effect, two central elements of psychometrics, reliability and validity, will be discussed in detail. Rather than assert a position as to whether the scores derived from putative measures of EI may or may not be associated with adequate levels of reliability and/or validity, this chapter will focus primarily on the description of contemporary approaches to the assessment of reliability and validity. However, in many cases, comments specifically relevant to the area of EI will be made within the context of reliability and/or validity assessment.

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Notes

  1. 1.

    Occasionally read in the contemporary literature is internal consistency reliability based on the Kuder–Richardson 20 formula. The KR20 reliability procedure predates Cronbach’s α, but was limited to dichotomously scored items from which “proportion correct” and “proportion incorrect” information could be derived for each item. When the items are of equal difficulty, a more simplified formulation can be used to estimate reliability (i.e., KR21).

  2. 2.

    \(\omega _A = \displaystyle\frac{{\sum {(.70 + .70 + .70)^2 } }}{{\sum {(.70 + .70 + .70)^2 + (} .51 + .51 + .51)}} = \frac{{2.10^2 }}{{2.10^2 + 1.53}} = \frac{{4.41}}{{5.94}} = .74\)

  3. 3.

    Of course, the interface between validity and reliability is further blurred by the close correspondence between factorial validity and internal consistency reliability.

  4. 4.

    Some investigators have erroneously equated true scores with constructs scores (e.g., Schmidt & Hunter, 1999). It should be noted that scores devoid of measurement error (i.e., true scores) are not necessarily scores associated with any construct validity (Borsboom & Mellenbergh, 2002).

  5. 5.

    While it is true that split-half reliability estimates and Cronbach’s α estimates will not usually yield the same values, such a large discrepancy can not reasonably be expected to be due to the different formulations.

  6. 6.

    Technically, the Vocabulary measure consisted of only 60% of the items of a full Vocabulary subtest, as only 30 of the 50 items from the standard Vocabulary subtest were chosen in the Mayer, Caruso, and Salovey (2000) study.

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Authors and Affiliations

  1. School of Psychology, University of Western Australia, Crawley, WA, 6009, Australia

    Gilles E. Gignac

  2. Director of Research & Development, Genos Pty Ltd, Suite 1.11/365 Little Collins Street, Melbourne VIC 3000, Australia

    Gilles E. Gignac

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    Gignac, G.E. (2009). Psychometrics and the Measurement of Emotional Intelligence. In: Parker, J., Saklofske, D., Stough, C. (eds) Assessing Emotional Intelligence. The Springer Series on Human Exceptionality. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-88370-0_2

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