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      Die Dunkle Triade in einer deutschen repräsentativen Stichprobe : Faktorstruktur, Messinvarianz und Normwerte der Niederträchtigen Neun

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          Abstract

          Zusammenfassung. Die „Niederträchtigen Neun“ ist eine psychometrisch optimierte deutsche Version des „Dreckigen Dutzends“ zur Erfassung der Dunklen Triade. In dieser Studie betrachten wir diverse psychometrische Eigenschaften der Niederträchtigen Neun mit einer repräsentativen deutschen Stichprobe. Es wurden verschiedene Faktorstrukturen miteinander verglichen sowie Messinvarianzanalysen über das Geschlecht und über das Alter anhand von konfirmatorischen Faktoranalysen und lokal gewichteten Strukturgleichungsmodellen durchgeführt. Außerdem stellen wir Normwerte zur individualdiagnostischen Interpretation von Rohwerten zur Verfügung. Ergebnisse zeigen, dass die Niederträchtigen Neun durch Bifaktor-Modelle mit Machiavellismus als inhaltlicher Anker des allgemeinen Faktors (dem „dunklen Kern“) am besten repräsentiert wird. Über das Geschlecht ergaben sich Einschränkungen der metrischen Invarianz, die hauptsächlich auf Indikatoren von Psychopathie zurückzuführen sind. Partielle metrische Invarianz konnte jedoch belegt werden. Über das Alter konnte metrische Invarianz belegt werden, jedoch ergaben sich Einschränkungen der skalaren und strikten Invarianz. Implikationen für die Erfassung der Dunklen Triade mit der Niederträchtigen Neun oder dem Dreckigen Dutzend werden diskutiert.

          The Dark Triad in a German Representative Sample. Factor Structure, Measurement Invariance, and Reference Values of the Naughty Nine

          Abstract. The so-called “Naughty Nine” is a psychometrically optimized German version of the “Dirty Dozen”, a scale designed to assess the Dark Triad. This article examines different psychometric features of the Naughty Nine using a representative German sample. We compared several factor structures discussed in the literature and investigated measurement invariance across sex and age, using confirmatory factor analyses and locally weighted structural equation models. Further, we provide reference values for the Naughty Nine to rank individual raw values relative to a German reference population. The results show that bifactor models with Machiavellianism as the reference construct that defines the content of the general factor (the “Dark Core”) best represent the Naughty Nine. We found limitations of metric invariance across sex, which can mainly be attributed to indicators of psychopathy. Partial metric invariance was supported. Across age, we found evidence for metric invariance but also found limitations of scalar and strict invariance. Finally, we discuss the implications of investigating the Dark Triad using the Naughty Nine or the Dirty Dozen.

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          Most cited references42

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          lavaan: AnRPackage for Structural Equation Modeling

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            Comparative fit indexes in structural models.

            Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model. A drawback of existing indexes is that they estimate no known population parameters. A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models. Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes. CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI). FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI. Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom. All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics. An example illustrates the behavior of these indexes under conditions of correct specification and misspecification. The new fit indexes perform very well at all sample sizes.
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              Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance

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                Author and article information

                Contributors
                Journal
                dia
                Diagnostica
                Hogrefe Verlag, Göttingen
                0012-1924
                2190-622X
                January 2023
                05 September 2022
                : 69
                : 1
                : 1-13
                Affiliations
                [ 1 ]Fakultät für Psychologie, Ruhr-Universität Bochum, Deutschland
                Author notes
                Julia Krasko, Fakultät für Psychologie , Ruhr-Universität Bochum, Universitätsstr. 150, 44801 Bochum, Deutschland, julia.krasko@ 123456rub.de
                Author information
                https://orcid.org/0000-0002-8046-2330
                Article
                dia_69_1_1
                10.1026/0012-1924/a000292
                14bd8cbb-0b73-4f5b-9160-aabb078c59a1
                Distributed as a Hogrefe OpenMind article under the license CC BY 4.0 (https://creativecommons.org/licenses/by/4.0)

                Distributed as a Hogrefe OpenMind article under the license CC BY 4.0 ( https://creativecommons.org/licenses/by/4.0)

                History
                Funding
                Förderung: Open Access-Veröffentlichung ermöglicht durch die Ruhr-Universität Bochum.
                Categories
                Originalarbeit

                Psychology,Clinical Psychology & Psychiatry
                reference values,factor structure,measurement invariance,Dark Triad,Normwerte,Faktorstruktur,Messinvarianz,Dunkle Triade

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