Dr. Marie-Ann Sengewald


Contact:

Wilhelmsplatz 3, Raum 01.22
96047 Bamberg
Tel. +49(0)951-863-3678
Marie-Ann.Sengewald(at)uni-bamberg.de

Professional career

  • 2012-2017: Research associate, Department of Methodology and Evaluation Research, Friedrich Schiller University Jena
  • 2009-2011: Student research assistant at the project "Fair Comparisons in Educational Research"
  • 2007-2009: Student research assistant at the Department of Methodology and Evaluation Research, Friedrich Schiller University Jena
  • 2006-2009: Tutor for descriptive, inference and multivariate statistics at the Department of Methodology and Evaluation Research, Friedrich Schiller University Jena

Education

  • 2012 - 2019: Doctorate, dissertation topic "Latent Covariates", Freie Universität Berlin (advisors Steffi Pohl & Rolf Steyer)
  • 2005 - 2011: Studies in Psychology, Friedrich Schiller University Jena
  • 08/2009 - 01/2010: Human Development and Family Studies at the Pennsylvania State University

Research Interests

  • Causal Inference
  • Item response theory
  • Structural equation modeling
  • Replication research

Research Projects

Principal Investigators: Marie-Ann Sengewald, Steffi Pohl, Anne Gast & Mathias Twardawski
Project Staff: Jerome Hoffmann
Funding: German Research Foundation (SE 3287/1-1)
Duration: 2022-2025

 

Teaching

 Otto Friedrich University Bamberg

  • Methods of evaluation research
  • Multivariate statistics
  • Structural equation modeling
  • Research internship: test construction

 Friedrich Schiller University Jena

  • Introduction to latent variable modeling
  • Item response theory
  • Bachelorpropädeutikum

My classes are supported by DataCamp.

Publications

  • Gnambs, T., & Sengewald, M.-A. (in press). Meta-analytic structural equation modeling with fallible measurements. Zeitschrift für Psychologie. Accepted for publication. preprint
  • Sengewald, M.-A., & Mayer, A. (2022). Causal effect analysis in non-randomized data with latent variables and categorical indicators: The implementation and benefits of EffectLiteR.
    Psychological Methods
    . Advance online publication. https://doi.org/10.1037/met0000489
  • Sengewald, M.-A., & Pohl, S. (2019). Compensation and amplification of attenuation bias in causal effect estimates. Psychometrika.84(2), 589-610. https://doi.org/10.1007/s11336-019-09665-6
  • Sengewald, M.-A., Pohl, S., & Steiner, P. M. (2019). When does measurement error in covariates impact causal effect estimates? - Analytical derivations of different scenarios and an empirical illustration. British Journal of Mathematical and Statistical Psychology. 72(2), 244-270.

    https://doi.org/10.1111/bmsp.12146

  • Thielemann, D., Sengewald, M.-A., Kappler, G., & Steyer, R. (2017). A probit latent state IRT model with latent item-effect variables. European Journal of Psychological Assessment.33(4), 271-284. https://doi.org/10.1027/1015-5759/a000417

  • Gast, A., Langer, S., Sengewald, M.-A. (2016). Evaluative conditioning increases with temporal contiguity. The influence of stimulus order and stimulus interval on evaluative conditioning. Acta Psychologica. 170, 177-185. https://doi.org/10.1016/j.actpsy.2016.07.002

  • Pohl, S., Sengewald, M.-A., & Steyer, R. (2016) Adjustment when covariates are fallible. In W. Wiedermann & A. v. Eye (Eds.), Statistics and causality: Methods for applied empirical research. New Jersey: Wiley.

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