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Establishing the structure and replicability of personality profiles using the HEXACO-PI-R


Previous attempts to identify personality profiles in the five-factor and HEXACO models of personality have produced inconsistent results. Here, using data from four independent samples, each with approximately 90,000 international respondents to the 100-item HEXACO Personality Inventory-Revised (HEXACO-PI-R), we demonstrated that a five-profile solution fit the data well. Exploratory analyses suggested that this solution was also consistent across gender and age groups. The five-profile structure replicated well with larger subsamples, but could not be reproduced consistently with samples of fewer than 500 individuals. However, even with small samples, the five-profile structure could be applied using the parameters obtained with the larger samples. We used HEXACO theory along with agency–communion and attachment theories to offer preliminary explanations and labels for the five profiles. We discuss how these theories, combined with parameter estimates provided by our research, can be used to generate and test hypotheses to validate the five-profile structure and evaluate its utility for personality research and other applications.

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Fig. 1: Number of profiles suggested by statistical indicators.
Fig. 2: Means of the six HEXACO scales for the five-profile solution.
Fig. 3: Means of the six HEXACO scales for the seven-profile solution.
Fig. 4: Means of the six HEXACO scales for the nine-profile solution.
Fig. 5: Mean absolute values of parameter deviations from the optimal five-profile solution.

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Data availability

The data that support the findings of this study were used with permission from K. Lee and M. Ashton56 and are not publicly available. Requests for access to the data should be directed to K. Lee and M. Ashton.

Code availability

Syntax required for the use of the final factor structure and optimal profile solution identified in this research are available in the Supplementary Software for this paper and online in the form of Mplus.inp files ( Syntax is provided for use in Mplus 7.0 or above and annotations describe the functions of different sections of the code.


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The authors thank K. Lee and M. Ashton for sharing the data used in this research and for their comments on an earlier version of this manuscript. This research was supported by funding to J.P.M. from the Social Sciences Faculty Research Development Grant (2018–19) at The University of Western Ontario. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Authors and Affiliations



K.N.D., J.P.M. and J.A.E. conceptualized the research, interpreted results and wrote the manuscript. J.A.E. and K.N.D. designed the methods and performed the analyses. J.A.E. and K.N.D. contributed equally to this article and both should be considered first authors.

Corresponding authors

Correspondence to Jose A. Espinoza or Kabir N. Daljeet.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–4, Supplementary Tables 1–8, methods and results.

Reporting Summary

Supplementary Software 1

Supplementary_Software_1.inp—Code for Imposing factor structure and extracting factor scores; Supplementary_Software_2.inp—Code for imposing the 5-profile solution and extracting class probabilities; Supplementary_Software_3.xlsx—Information for converting the item names used in the 2 other supplementary software files to other naming conventions in other datasets.

Supplementary Software 2

File with detailed guidelines on using the Supplementary Software files.

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Espinoza, J.A., Daljeet, K.N. & Meyer, J.P. Establishing the structure and replicability of personality profiles using the HEXACO-PI-R. Nat Hum Behav 4, 713–724 (2020).

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