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Dr. Tamara Schamberger

Campus der Universität Bielefeld — © Universität Bielefeld

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Head

Prof. Dr. Christiane Fuchs

Room V9 - 132
Phone +49 521 106-2576
Email christiane.fuchs@uni-bielefeld.de

Office

Angelika Gerent

Room V9 - 138
Phone +49 521 106-6930
Email agerent@uni-bielefeld.de

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If you are interested in a position as postdoctoral researcher, doctoral student or student assistant, please contact us!

Dr. Tamara Schamberger

Postdoctoral Researcher

Email
tamara.schamberger@uni-bielefeld.de

Room
V9-134

Phone
+49 521 106-4877

Research Interests

Structural equation modeling
Emergent variables
Maximum likelihood estimation

Published Papers

Schuberth, F., Schamberger, T., Henseler, J. (2023). More powerful parameter tests? No, rather biased parameter estimates. Some reflections on path analysis with weighted composites. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02256-5
Schuberth, F., Hubona, G., Roemer, E., Zaza, S., Schamberger, T., Chuah, F., Cepeda-Carrión, G., Henseler, J. (2023). The choice of structural equation modeling technique matters: A commentary on Dash and Paul (2021). Technological Forecasting and Social Change, 194, 122665
Schamberger, T. (2023). Conducting Monte Carlo Simulations for PLS-PM and other variance-based estimators for structural equation modeling. Industrial Management & Data Systems, 123(6), 1789-1813, https://doi.org/10.1108/IMDS-07-2022-0418
Schuberth, F., Schamberger, T., Rönkkö, M., Liu, Y., Henseler, J. (2023). Premature Conclusions about the Signal-to-Noise Ratio in Structural Equation Modeling Research: A Commentary on Yuan and Fang (2023). British Journal of Mathematical and Statistical Psychology, http://doi.org/10.1111/bmsp.12304
Schamberger, T. (2022) Methodological Advances in Composite-based Structural Equation Modeling. University of Würzburg/ University of Twente, https://doi.org/10.3990/1.9789036553759
Schamberger, T., Cantaluppi, G., Schuberth, F. (accepted). Revisiting and Extending PLS for Ordinal Measurement and Prediction In H. Latan, J. F. Hair, & R. Noonan (Eds.), Partial least squares path modeling: Basic concepts, methodological issues, and applications (2nd ed.). Cham, Switzerland: Springer.
Schamberger, T., Schuberth, F., & Henseler, J. (2023). Confirmatory composite analysis in human development research. International Journal of Behavioral Development, 47(1), 89–100. https://doi.org/10.1177/01650254221117506
Schamberger, T., Schuberth, F., Henseler, J., Dijkstra T. K. (2020). Robust partial least squares path modeling. Behaviormetrika, https://doi.org/10.1007/s41237-019-00088-2

Teaching

Zeitreihenanalyse Vorlesung (Sommer 2024)
Zeitreihenanalyse Praktische Übung (Sommer 2024)
Grundlagen der Statistik (Winter 2023)
Introduction to Structural Equation Modeling (Winter 2023)

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Curriculum vitae

Since 07/2023	Postdoctoral Researcher Data Science Group Faculty of Business Administration and Economics, Bielefeld University
08/2022 – 06/2023	Postdoctoral Researcher Chair of Econometrics Faculty of Business Management and Economics, University of Würzburg
10/2017 – 07/2022	PhD student Chair of Econometrics Faculty of Business Management and Economics, University of Würzburg; Chair of Product Market Relations Faculty of Engineering Technology, University of Twente
10/2015 – 09/2017	M.Sc. in Economathematics, University of Würzburg
10/2012 – 09/2015	B.Sc. in Economathematics, University of Würzburg