Prof. Dr. Matthias Ziegler
Profil
Zusammenfassung
Prof. Ziegler entwickelt und validiert psychometrische Messinstrumente für Persönlichkeit, Intelligenz und Kompetenzen. Seine Expertise liegt in der statistischen Überprüfung von Testqualität, der Modellierung von Antwortverfälschungen und der Analyse von Persönlichkeits-Situations-Interaktionen. Diese Kompetenzen sind für Unternehmen relevant, die valide Assessments für Personalauswahl und -entwicklung benötigen.
Skills
Stammdaten
Identität, Organisation und Kontakt aus HU-FIS.
Forschungsthemen18
Analyse der bisher im TestLab durchgeführten Projekte durch und erstellt basierend auf der Analyse eine Wissensdatenbank
Quelle ↗Förderer: Andere Hochschulfördergesellschaften Zeitraum: 08/2009 - 09/2009 Projektleitung: Prof. Dr. Matthias Ziegler
Angebot über psychometrisches Screening von Kompetenztest-Items
Quelle ↗Förderer: Bertelsmann-Stiftung Zeitraum: 10/2016 - 10/2017 Projektleitung: Prof. Dr. Matthias Ziegler
AvH Baghaei Moghadam
Quelle ↗Förderer: Alexander von Humboldt-Stiftung Zeitraum: 07/2015 - 09/2015 Projektleitung: Prof. Dr. Matthias Ziegler
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Publikationen25
Top 25 nach Zitationen — Quelle: OpenAlex (BAAI/bge-m3 embedded für Matching).
Methodology · 1248 Zitationen · DOI
Empirical evidence to the robustness of the analysis of variance (ANOVA) concerning violation of the normality assumption is presented by means of Monte Carlo methods. High-quality samples underlying normally, rectangularly, and exponentially distributed basic populations are created by drawing samples which consist of random numbers from respective generators, checking their goodness of fit, and allowing only the best 10% to take part in the investigation. A one-way fixed-effect design with three groups of 25 values each is chosen. Effect-sizes are implemented in the samples and varied over a broad range. Comparing the outcomes of the ANOVA calculations for the different types of distributions, gives reason to regard the ANOVA as robust. Both, the empirical type I error α and the empirical type II error β remain constant under violation. Moreover, regression analysis identifies the factor “type of distribution” as not significant in explanation of the ANOVA results.
Journal of Personality and Social Psychology · 605 Zitationen · DOI
Taxonomies of person characteristics are well developed, whereas taxonomies of psychologically important situation characteristics are underdeveloped. A working model of situation perception implies the existence of taxonomizable dimensions of psychologically meaningful, important, and consequential situation characteristics tied to situation cues, goal affordances, and behavior. Such dimensions are developed and demonstrated in a multi-method set of 6 studies. First, the "Situational Eight DIAMONDS" dimensions Duty, Intellect, Adversity, Mating, pOsitivity, Negativity, Deception, and Sociality (Study 1) are established from the Riverside Situational Q-Sort (Sherman, Nave, & Funder, 2010, 2012, 2013; Wagerman & Funder, 2009). Second, their rater agreement (Study 2) and associations with situation cues and goal/trait affordances (Studies 3 and 4) are examined. Finally, the usefulness of these dimensions is demonstrated by examining their predictive power of behavior (Study 5), particularly vis-à-vis measures of personality and situations (Study 6). Together, we provide extensive and compelling evidence that the DIAMONDS taxonomy is useful for organizing major dimensions of situation characteristics. We discuss the DIAMONDS taxonomy in the context of previous taxonomic approaches and sketch future research directions.
Psychological Methods · 420 Zitationen · DOI
Fit indices are widely used in order to test the model fit for structural equation models. In a highly influential study, Hu and Bentler (1999) showed that certain cutoff values for these indices could be derived, which, over time, has led to the reification of these suggested thresholds as "golden rules" for establishing the fit or other aspects of structural equation models. The current study shows how differences in unique variances influence the value of the global chi-square model test and the most commonly used fit indices: Root-mean-square error of approximation, standardized root-mean-square residual, and the comparative fit index. Using data simulation, the authors illustrate how the value of the chi-square test, the root-mean-square error of approximation, and the standardized root-mean-square residual are decreased when unique variances are increased although model misspecification is present. For a broader understanding of the phenomenon, the authors used different sample sizes, number of observed variables per factor, and types of misspecification. A theoretical explanation is provided, and implications for the application of structural equation modeling are discussed.
Kooperationen3
Bestätigte Forscher↔Partner-Paare aus HU-FIS — Gold-Standard-Positive für das Matching.
GRK 2434: Facetten der Komplexität
university
GRK 2434: Facetten der Komplexität
university
Moral Exceptionality in Daily Life: Antecedents, Dynamics, and Consequences of Morally Exceptional Person-Situation Transactions
university