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Fakultät Statistik
Studenten im Sommer auf dem Campus Nord, rote Zahnräder im Hintergrund © Roland Baege​/​TU Dortmund
PROMOVIERENDE

Marie Beisemann

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Technische Uni­ver­si­tät Dort­mund
Fa­kul­tät Sta­tis­tik
Lehrstuhl für Statistische Methoden in den Sozialwissenschaften
Mathe­matik, Raum 715
44221 Dort­mund

E-Mail: beisemannstatistik.tu-dortmundde
Tel.: 0231 755 - 8327

Foto von Marie Beisemann © Marie Beisemann​/​privat

Forschungsinteressen

  • Psychometrie und Item Response Theory
  • Zähldaten
  • Kreatives Denken
  • Meta-Analyse

Publikationen

  • Hahn, T., Winter, N. R., Ernsting, J., Gruber, M., Mauritz, M. J., Fisch, L., ..., Beisemann, M., ... & Repple, J. (2023). Genetic, individual, and familial risk correlates of brain network controllability in major depressive disorder. Molecular Psychiatry, 1-7. https://doi.org/10.1038/s41380-022-01936-6

  • Büscher, R., Beisemann, M., Doebler, P., Micklitz, H. M., Kerkhof, A., Cuijpers, P., ... & Sander, L. B. (2022). Digital cognitive–behavioural therapy to reduce suicidal ideation and behaviours: A systematic review and meta-analysis of individual participant data. Evidence-Based Mental Health, 25(e1), e8-e17. https://ebmh.bmj.com/content/25/e1/e8

  • Blötner, C.*, & Beisemann, M.* (2022). The Dark Triad is Dead, Long Live the Dark Triad: An Item-Response Theoretical Examination of the Short Dark Tetrad. Personality and Individual Differences, 199, 111858. doi:10.1016/j.paid.2022.111858 [*Geteilte Erstautorenschaft]

  • Beisemann, M. (2022). A flexible approach to modelling over‐, under‐and equidispersed count data in IRT: The Two‐Parameter Conway–Maxwell–Poisson Model. British Journal of Mathematical and Statistical Psychology. (Advance online publication.) https://doi.org/10.1111/bmsp.12273

  • Hahn, T., Ernsting, J., Winter, N. R., Holstein, V., Leenings, R., Beisemann, M., ... & Berger, K. (2022). An uncertainty-aware, shareable, and transparent neural network architecture for brain-age modeling. Science advances, 8(1), eabg9471.
  • Beisemann, M.*, Wartlick, O.*, & Doebler, P. (2020). Comparison of Recent Acceleration Techniques for the EM algorithm in One-and Two-Parameter Logistic IRT models. Psych, 2(4), 209-252. doi:10.3390/psych2040018 [* Geteilte Erstautorenschaft.]
  • Büscher, R., Beisemann, M., Doebler, P., Steubl, L., Domhardt, M., Cuijpers, P., ... & Sander, L. B. (2020). Effectiveness of internet-and mobile-based cognitive behavioral therapy to reduce suicidal ideation and behaviors: protocol for a systematic review and meta-analysis of individual participant data. International journal of environmental research and public health, 17(14), 5179.
  • Beisemann, M., Doebler, P., & Holling, H. (2020). Comparison of random‐effects meta‐analysis models for the relative risk in the case of rare events: A simulation study. Biometrical Journal. 1– 34. doi:10.1002/bimj.201900379
  • Beisemann, M., Forthmann, B., Bürkner, P. C., & Holling, H. (2019). Psychometric evaluation of an alternate scoring for the remote associates test. The Journal of Creative Behavior. doi:10.1002/jocb.394
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