Dr. Tamara Schamberger

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)

Links

Google Scholar

GitHub

ORCID

Researchgate

Curriculum vitae