Hector Research Institute of Education Sciences and Psychology

Prof. Dr. Elisabeth Kraus

Elisabeth Kraus is a junior professor of methods in empirical educational research. Her interests are diverse and encompass (almost) all types of data modeling. Her research focuses on psychometrics, the use of machine learning in educational research, and the utilization of evaluation study data for individual training recommendations. In her research, she aims not only to develop new methods and approaches but also to put them into practice.

Address

University of Tübingen
Hector Research Institute of Education Sciences and Psychology
72072 Tübingen, Germany
Room 404

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Publikationen

Publikationen

Bayer, L., Cigelski, M., Eilfgang, J., Kraus, E. B., Mensing, F., & Pülschen, S. (2025). German version of
the child sexual abuse myth scale (CSAMS-G): Translation, expansion, and construct validation.
Behavioral Sciences, 15(2). https://doi.org/10.3390/bs15020143 

Giglberger, M., Peter, H. L., Henze, G.-I., Kraus, E., Bärtl, C., Konzok, J., Zänkert, S., Kreuzpointner, L.,
Kirsch, P., Kudielka, B. M., et al. (2024). Brain activation changes as predictors for perceived stress and
cortisol awakening responses over a 13-months stress period. Psychoneuroendocrinology, 160, 106798.

Hrabetz, B., Kraus, E. B., & Gruber, H. (2024). Social identity in environmental protection engagement:
How are different kinds of identity related to different types of engagement? Journal of Applied Social
Psychology, 54, 776–786. https://doi.org/https://doi.org/10.1111/jasp.13072786 

Kraus, E., & Kern, C. (2024). Measurement modeling of predictors and outcomes in algorithmic
fairness. European Workshop on Algorithmic Fairness. 3(23), 1-18

Kraus, E., Wild, J., Bühner, M., Schilcher, A., & Hilbert, S. (2024). Applying cross-validated psychometric
models to the bavarian reading test (BYLET). European Journal of Psychological Assessment.
https://doi.org/https://doi.org/10.1027/1015-5759/a000848 

Kraus, E. B., Wild, J., & Hilbert, S. (2024b). Using interpretable machine learning for differential item
functioning detection in psychometric tests. Applied Psychological Measurement, 48(4-5), 167–186.
https://doi.org/10.1177/01466216241238744 

Sterner, P., Friemelt, B., Goretzko, D., Kraus, E. B., Bühner, M., & Pargent, F. (2024). The
confidence/significance level implies a certain cost ratio between type I error and type II error: For a
stronger focus on decision theory in psychological assessment-Das Konfidenz-/Signifikanzniveau
impliziert ein bestimmtes Kostenverhältnis zwischen Fehler 1. Art und Fehler 2. Art: Für ein stärkeres
Einbeziehen der Entscheidungstheorie in die psychologische Einzelfalldiagnostik. Diagnostica, 70(3),
126–138. https://doi.org/10.1026/0012-1924/a000329 

Giglberger, M., Peter, H. L., Henze, G.-I., Kraus, E., Bärtl, C., Konzok, J., Kreuzpointner, L., Kirsch, P.,
Kudielka, B. M., & Wüst, S. (2023). Neural responses to acute stress predict chronic stress perception in
daily life over 13 months. Scientific Reports, 13(1), 19990. https://doi.org/https://doi.org/10.1016/j.psyneuen.2022.105771 

Kraus, E. B. (2022). Diagnostische Entscheidungen mit dem Treatment Decision Model – ein
entscheidungstheoretischer Ansatz auf Basis von Evaluationsstudiendaten. LMU Munich, Germany

Giglberger, M., Peter, H. L., Kraus, E., Kreuzpointner, L., Zänkert, S., Henze, G.-I., Bärtl, C., Konzok, J.,
Kirsch, P., Rietschel, M., et al. (2022). Daily life stress and the cortisol awakening response over a
13-months stress period–findings from the lawstress project. Psychoneuroendocrinology, 141, 105771.

Hilbert, S., Pargent, F., Kraus, E., Naumann, F., Eichhorn, K., Ungar, P., & Bühner, M. (2022). What’s the
measure? An empirical investigation of self-ratings on response scales. International Journal of Social
Research Methodology, 25(1), 59–78.

Schilcher, A., Wild, J., Kraus, E., & Hilbert, S. (2022). FiLBY-2–ein Leseflüssigkeitstraining für alle
Schülerinnen und Schüler? Differenzielle Effekte. Zeitschrift für Sprachlich-Literarisches Lernen und
Deutschdidaktik, 2.

Hilbert, S., Coors, S., Kraus, E., Bischl, B., Lindl, A., Frei, M., Wild, J., Krauss, S., Goretzko, D., &
Stachl, C. (2021). Machine Learning for the educational sciences. Review of Education, 9(3), e3310.

Curriculum Vitae

Since 03/2025
Junior Professor at the Hector Research Institute of Education Sciences and Psychology

Methods in Empirical Educational Research, University of Tübingen

04/2023 - 02/2025
Postdoc

Computational Modelling in Psychology, LMU Munich

10/2020 - 03/2023
Master of Science in Statistics

LMU Munich

03/2018 - 03/2023
Research Associate

Educational Data Science, University of Regensburg

03/2018 - 11/2022
Doctoral Studies: Psychology

LMU Munich

10/2015 - 08/2017
Master of Science in Psychology: Learning Sciences

LMU Munich

10/2011 - 08/2015
Bachelor of Science in Psychology

University of Freiburg

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