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      The Big Five Inventory (BFI) : Reliability and Validity of its Italian Translation in Three Independent Nonclinical Samples

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          Abstract

          The internal consistency reliability, factor structure, and convergent-discriminant validity of the Italian translation of the Big Five Inventory (BFI) were assessed in two independent samples of nonclinical adult volunteers (Sample 1: N = 500; Sample 2: N = 316) and in one sample of adolescent volunteers (Sample 3: N = 223). Two adult subsamples ( n = 70, and n = 141, respectively) also provided 2-month retest reliability data. The internal consistency reliabilities were adequate for all five BFI scales (mean α values were .77, .78, and .81 for Sample 1, Sample 2, and Sample 3, respectively); all test-retest correlations were greater than .75 in both adult participant subsamples. Principal component analyses showed that only the first five components of the BFI item correlation matrix could be reproduced safely across the three samples. The BFI scales showed adequate convergent-discriminant validity coefficients in all three samples. These findings suggest that the BFI is a succinct measure of the Big Five personality traits and it provides satisfactory reliability and validity data.

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          Personality and job performance: The Big Five revisited.

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            Remarks on Parallel Analysis.

            We investigate parallel analysis (PA), a selection rule for the number-of-factors problem, from the point of view of permutation assessment. The idea of applying permutation test ideas to PA leads to a quasi-inferential, non-parametric version of PA which accounts not only for finite-sample bias but sampling variability as well. We give evidence, however, that quasi-inferential PA based on normal random variates (as opposed to data permutations) is surprisingly independent of distributional assumptions, and enjoys therefore certain non- parametric properties as well. This is a justification for providing tables for quasi-inferential PA. Based on permutation theory, we compare PA of principal components with PA of principal factor analysis and show that PA of principal factors may tend to select too many factors. We also apply parallel analysis to so-called resistant correlations and give evidence that this yields a slightly more conservative factor selection method. Finally, we apply PA to loadings and show how this provides benchmark values for loadings which are sensitive to the number of variables, number of subjects, and order of factors. These values therefore improve on conventional fixed thresholds such as 0.5 or 0.8 which are used irrespective of the size of the data.
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              Ascertaining the validity of individual protocols from Web-based personality inventories

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                Author and article information

                Journal
                jpa
                European Journal of Psychological Assessment
                Hogrefe Publishing
                1015-5759
                2151-2426
                January 2011
                : 27
                : 1
                : 50-58
                Affiliations
                [ 1 ] School of Psychology, San Raffale Vita-Salute University, Milano, Italy
                Author notes
                Andrea Fossati, Servizio di Psicologia Clinica e Psicoterapia, San Raffaele Turro, via Stamira d’Ancona 20, I-20127 Milano, Italy, +39 02 26433241, +39 02 26433408, fossati.andrea@ 123456hsr.it
                Article
                jpa_27_1_50
                10.1027/1015-5759/a000043
                efbfabd8-c106-447a-ab26-a4d077d891a1
                Copyright @ 2011
                History
                Categories
                Original Article

                Assessment, Evaluation & Research methods,Psychology,General behavioral science
                reliability,Big Five,personality,validity

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