Literature DB >> 27637740

Modeling General, Specific, and Method Variance in Personality Measures: Results for ZKA-PQ and NEO-PI-R.

Francisco J Abad1, Miguel A Sorrel1, Luis Francisco Garcia1,2, Anton Aluja2,3.   

Abstract

Contemporary models of personality assume a hierarchical structure in which broader traits contain narrower traits. Individual differences in response styles also constitute a source of score variance. In this study, the bifactor model is applied to separate these sources of variance for personality subscores. The procedure is illustrated using data for two personality inventories-NEO Personality Inventory-Revised and Zuckerman-Kuhlman-Aluja Personality Questionnaire. The inclusion of the acquiescence method factor generally improved the fit to acceptable levels for the Zuckerman-Kuhlman-Aluja Personality Questionnaire, but not for the NEO Personality Inventory-Revised. This effect was higher in subscales where the number of direct and reverse items is not balanced. Loadings on the specific factors were usually smaller than the loadings on the general factor. In some cases, part of the variance was due to domains being different from the main one. This information is of particular interest to researchers as they can identify which subscale scores have more potential to increase predictive validity.

Keywords:  Big Five structure; NEO-PI-R; ZKA-PQ; bifactor model; response styles

Mesh:

Year:  2016        PMID: 27637740     DOI: 10.1177/1073191116667547

Source DB:  PubMed          Journal:  Assessment        ISSN: 1073-1911


  4 in total

1.  A genetic algorithm for optimal assembly of pairwise forced-choice questionnaires.

Authors:  Rodrigo Schames Kreitchmann; Francisco J Abad; Miguel A Sorrel
Journal:  Behav Res Methods       Date:  2021-09-09

2.  Searching for G: A New Evaluation of SPM-LS Dimensionality.

Authors:  Eduardo Garcia-Garzon; Francisco J Abad; Luis E Garrido
Journal:  J Intell       Date:  2019-06-28

3.  Controlling for Response Biases in Self-Report Scales: Forced-Choice vs. Psychometric Modeling of Likert Items.

Authors:  Rodrigo Schames Kreitchmann; Francisco J Abad; Vicente Ponsoda; Maria Dolores Nieto; Daniel Morillo
Journal:  Front Psychol       Date:  2019-10-15

4.  Modeling Wording Effects Does Not Help in Recovering Uncontaminated Person Scores: A Systematic Evaluation With Random Intercept Item Factor Analysis.

Authors:  María Dolores Nieto; Luis Eduardo Garrido; Agustín Martínez-Molina; Francisco José Abad
Journal:  Front Psychol       Date:  2021-06-02
  4 in total

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