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Book cover: Research on Emotion in Organizations

Research on Emotion in Organizations

ISSN: 1746-9791
Series editor(s): Neal M. Ashkanasy, Wilfred J. Zerbe and Charmine E. J. Härtel

Subject Area: Organization Studies

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Chapter 11 The Measurement of Trait Emotional Intelligence with TEIQue-SF: An Analysis Based on Unfolding Item Response Theory Models


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Title:Chapter 11 The Measurement of Trait Emotional Intelligence with TEIQue-SF: An Analysis Based on Unfolding Item Response Theory Models
Author(s):Leonidas A. Zampetakis
Volume:7 Editor(s): Charmine E.J. Härtel, Neal M. Ashkanasy, Wilfred J. Zerbe ISBN: 978-1-78052-208-1 eISBN: 978-1-78052-209-8
Citation:Leonidas A. Zampetakis (2011), Chapter 11 The Measurement of Trait Emotional Intelligence with TEIQue-SF: An Analysis Based on Unfolding Item Response Theory Models, in Charmine E.J. Härtel, Neal M. Ashkanasy, Wilfred J. Zerbe (ed.) What Have We Learned? Ten Years On (Research on Emotion in Organizations, Volume 7), Emerald Group Publishing Limited, pp.289-315
DOI:10.1108/S1746-9791(2011)0000007016 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Article type:Chapter Item
Abstract:The present chapter addresses a topic that is of growing interest – namely, the exploration of alternative item response theory (IRT) models for noncognitive assessment. Previous research in the assessment of trait emotional intelligence (or “trait emotional self-efficacy”) has been limited to traditional psychometric techniques (e.g., classical test theory) under the notion of a dominance response processes describing the relationship between individuals' latent characteristics and individuals' response selection. The present study, presents the first unfolding IRT modeling effort in the general field of emotional intelligence (EI). We applied the Generalized Graded Unfolding Model (GGUM) in order to evaluate the response process and the item properties on the short form of the trait emotional intelligence questionnaire (TEIQue-SF). A sample of 866 participants completed the English version of the TEIQue-SF. Results suggests that the GGUM has an adequate fit to the data. Furthermore, inspection of the test information and standard error functions revealed that the TEIQue-SF is accurate for low and middle scores on the construct; however several items had low discrimination parameters. Implications for the benefits of unfolding models in the assessment of trait EI are discussed.

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