Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/1015
Title: The HEXACO–100 Across 16 Languages: A Large-Scale Test of Measurement Invariance
Authors: Thielmann I.
Akrami N.
Babarović T.
Belloch A.
Bergh R.
Chirumbolo A.
Čolović, Petar 
de Vries R.
Dostál D.
Egorova M.
Gnisci A.
Heydasch T.
Hilbig B.
Hsu K.
Izdebski P.
Leone L.
Marcus B.
Međedović J.
Nagy J.
Parshikova O.
Perugini M.
Petrović, Bojan
Romero E.
Sergi I.
Shin K.
Smederevac, Snežana 
Šverko I.
Szarota P.
Szirmák Z.
Tatar A.
Wakabayashi A.
Wasti S.
Záškodná T.
Zettler I.
Ashton M.
Lee K.
Issue Date: 1-Jan-2019
Journal: Journal of Personality Assessment
Abstract: © 2019, © 2019 Taylor & Francis Group, LLC. 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.
URI: https://open.uns.ac.rs/handle/123456789/1015
ISSN: 00223891
DOI: 10.1080/00223891.2019.1614011
Appears in Collections:FF Publikacije/Publications

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