Publikationen

Publikationen mit Peer Review

(* kennzeichnet studentische Co-Autoren unter Supervision von Prof. Dr. Marie-Ann Sengewald)

2025

  • Edelsbrunner, P. A., Tetzlaff, L., Bach, K. M., Dumas, D., Hofer, S. I., Köhler, C., Kozlova, Z., Moeller, J., Reinhold, F., Roberts, G. J., Sengewald, M.-A., Bichler, S. (2025). Beyond linear regression: Statistically modeling aptitude-treatment interactions and the differential effectiveness of educational interventions. Learning and Individual Differences, 124, https://doi.org/10.1016/j.lindif.2025.102812.
  • Henninger, M., Radek, J., Sengewald, M.-A., & Strobl, C. (2025). Partial credit trees meet the partial gamma coefficient for quantifying DIF and DSF in polytomous items. Behaviormetrika, 52,  221–257. https://doi.org/10.1007/s41237-024-00252-3
  • Hoffmann*, J., Pohl, S., Twardawski, M., Gast, A., Höhs, J., & Sengewald, M.-A. (2025). Current practices for designing replications in social and cognitive psychology. Advances in Methods and Practices in Psychological Science, 8(2), 1-22.  https://doi.org/10.1177/25152459251328273
  • Kiefer, C. & Sengewald, M.-A. (2025). Mining exceptional Rasch models. Behaviormetrika, 52,  361–391. https://doi.org/10.1007/s41237-024-00251-4

2024

  • Hahn, I., & Sengewald, M.-A. (2024). NEPS Technical Report for science: Scaling results of Starting Cohort 1 for nine-year-old children (NEPS Survey Paper No. 116). Leibniz Institute for Educational Trajectories, National Educational Panel Study. https://doi.org/10.5157/NEPS:SP116:1.0
  • Hahn, I., & Sengewald, M.-A. (2024). NEPS Technical Report for science: Scaling results of Starting Cohort 1 for seven-year-old children (NEPS Survey Paper No. 115). Leibniz Institute for Educational Trajectories, National Educational Panel Study. https://doi.org/10.5157/NEPS:SP115:1.0
  • Heyne, N., Gnambs T. & Sengewald, M-A. (2024). Participation rates and differential effects of Extracurricular Tutoring Programs on Reading Literacy in a German Large-Scale Assessment. Large Scale Assessment in Education,  12, 27. https://doi.org/10.1186/s40536-024-00216-9
  • Sengewald, E., Hardt, K. & Sengewald, M.-A. (2024). A causal view on bias in missing data imputation: The impact of problematic auxiliary variables on the norming of test scores.  Multivariate Behavioral Research,  1-17. https://doi.org/10.1080/00273171.2024.2412682
  • Sengewald, M.-A., Henninger, M., Bechtloff, P., & Kubik, V. (2024). Familiengerechte Karrieremöglichkeiten in der psychologischen Forschung? Psychologische Rundschau, 75(3), 234-248. https://doi.org/10.1026/0033-3042/a000682
  • Sengewald, M.-A. & Mayer, A. (2024). Causal effect analysis in non-randomized data with latent variables and categorical indicators: The implementation and benefits of EffectLiteR. Psychological Methods, 29(2), 287-307. https://doi.org/10.1037/met0000489

2023

  • Erhardt*, T. H., Gnambs, T. & Sengewald, M-A. (2023). Studying item-effect variables and their correlation patterns with multi-construct multi-state models. PLoS ONE,  18(8): e0288711. https://doi.org/10.1371/journal.pone.0288711
  • Gnambs, T., & Sengewald, M.-A. (2023). Meta-analytic structural equation modeling with fallible measurements. Zeitschrift für Psychologie. 231(1), 39-52. https://doi.org/10.1027/2151-2604/a000511
  • Sengewald, M.-A., Erhardt*, T. E., & Gnambs, T. (2023). The predictive validity of item-effect variables in the satisfaction with life scale for psychological and physical health. Assessment, 30(8), 2461-2475. https://doi/10.1177/10731911221149949
  • Sengewald, M.-A., Hahn, I., & Kähler, J. (2023). NEPS Technical Report for science: Scaling results of Starting Cohorts 4 and 6 (wave 14) (NEPS Survey Paper No. 109). Leibniz Institute for Educational Trajectories, National Educational Panel Study. https://doi.org/10.5157/NEPS:SP109:1.0

2019

  • 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., Steiner, P. M., & Pohl, S. (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

2017

  • 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

2016

  • 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. von Eye (Hrsg.), Statistics and Causality: Methods for Applied Empirical Research (pp. 363-384). Hoboken, NJ: Wiley4

Präregistrierungen

(* kennzeichnet studentische Co-Autoren unter Supervision von Prof. Dr. Marie-Ann Sengewald)

  • Twardawski, M., Hoffmann*, J., Kondzic, D., Pohl, S., Gast, A., Höhs, J., & Sengewald, M.-A. (2023). Conceptual replications of the imagined intergroup contact effect. https://doi.org/10.17605/OSF.IO/EU64T
  • Gast, A., Höhs, J., Hoffmann*, J., Kondzic, D., Pohl, S., Twardawski, M., & Sengewald, M.-A. (2023). Impact of online vs. lab setting on the Evaluative Conditioning Effect – identification of causal effects of replication factors. https://osf.io/rvms3 
  • Hoffmann*, J., Pohl, S., Twardawski, M., Gast, A., Höhs, J., & Sengewald, M.-A.  (2022). Current practices for designing replications in social and cognitive psychology: A protocol for a systematic literature review and comparison.https://doi.org/10.17605/OSF.IO/YXGC8

Leitartikel

(# kennszeichnet geteilte Erstautorenschaft)

  • Kutscher#, T., Sengewald#, M.-A., Gnambs, T., Carstensen, C. & Aßmann, C. (2024). The National Educational Panel Study (NEPS) and Methodological Innovations in Longitudinal Large-Scale Assessments. Large Scale Assessment in Education.