The HEXACO–100 Across 16 Languages: A Large-Scale Test of Measurement Invariance

Isabel Thielmann*, Nazar Akrami, Toni Babarović, Amparo Belloch, Robin Bergh, Antonio Chirumbolo, Petar Čolović, Reinout E. de Vries, Daniel Dostál, Marina Egorova, Augusto Gnisci, Timo Heydasch, Benjamin E. Hilbig, Kung Yu Hsu, Paweł Izdebski, Luigi Leone, Bernd Marcus, Janko Međedović, János Nagy, Oksana ParshikovaMarco Perugini, Boban Petrović, Estrella Romero, Ida Sergi, Kang Hyun Shin, Snežana Smederevac, Iva Šverko, Piotr Szarota, Zsofia Szirmák, Arkun Tatar, Akio Wakabayashi, S. Arzu Wasti, Tereza Záškodná, Ingo Zettler, Michael C. Ashton, Kibeom Lee

*Corresponding author for this work
    11 Citations (Scopus)

    Abstract

    The HEXACO Personality Inventory–Revised (HEXACO–PI–R) has become one of the most heavily applied measurement tools for the assessment of basic personality traits. Correspondingly, the inventory has been translated to many languages for use in cross-cultural research. However, formal tests examining whether the different language versions of the HEXACO–PI–R provide equivalent measures of the 6 personality dimensions are missing. We provide a large-scale test of measurement invariance of the 100-item version of the HEXACO–PI–R across 16 languages spoken in European and Asian countries (N = 30,484). Multigroup exploratory structural equation modeling and confirmatory factor analyses revealed consistent support for configural and metric invariance, thus implying that the factor structure of the HEXACO dimensions as well as the meaning of the latent HEXACO factors is comparable across languages. However, analyses did not show overall support for scalar invariance; that is, equivalence of facet intercepts. A complementary alignment analysis supported this pattern, but also revealed substantial heterogeneity in the level of (non)invariance across facets and factors. Overall, results imply that the HEXACO–PI–R provides largely comparable measurement of the HEXACO dimensions, although the lack of scalar invariance highlights the necessity for future research clarifying the interpretation of mean-level trait differences across countries.

    Original languageEnglish
    JournalJournal of Personality Assessment
    ISSN0022-3891
    DOIs
    Publication statusPublished - 2 Sept 2020

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