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Source method biases as implicit personality theory at the domain and facet levels\n

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    0512001 - PSÚ 2020 RIV US eng J - Journal Article
    McCrae, R.R. - Mottus, R. - Hřebíčková, Martina - Realo, A. - Allik, J.
    Source method biases as implicit personality theory at the domain and facet levels
    .
    Journal of Personality. Roč. 87, č. 4 (2019), s. 813-826. ISSN 0022-3506. E-ISSN 1467-6494
    R&D Projects: GA ČR(CZ) GA17-14387S; GA ČR GA406/01/1507
    Institutional support: RVO:68081740
    Keywords : cross-cultural * measurement error * multimethod assessment * personality structure
    OECD category: Psychology (including human - machine relations)
    Impact factor: 3.667, year: 2019
    Method of publishing: Limited access
    https://onlinelibrary.wiley.com/doi/pdf/10.1111/jopy.12435

    Objective We tested predictions about the structure and magnitude of method biases in single-source personality trait assessments. We expected a large number of distinct biases that would parallel the observed structure of traits, at both facet and item levels. Method We analyzed multimethod ratings on the Estonian NEO Personality Inventory-3 in a sample of 3,214 adults. By subtracting informant ratings from self-reports, we eliminated true score variance and analyzed the size and structure of the residual method biases. We replicated analyses using data (N = 709) from the Czech Revised NEO Personality Inventory. Results The magnitude of method biases was consistent with predictions by McCrae (2018, Psychological Assessment). Factor analyses at the facet level showed a clear replication of the normative Five-Factor Model structure in both samples. Item factor analyses within domains showed that facet-level method biases mimicked the facet structure of the instrument. Conclusions Method biases apparently reflect implicit personality theory (IPT)-beliefs about how traits and trait indicators covary. We discuss the (collective) accuracy and possible origins of IPT. Because method biases limit the accuracy of single-source assessments, we recommend assessments that combine information from two or more informants.
    Permanent Link: http://hdl.handle.net/11104/0302228

     
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