1. 2021
  2. A semiparametric approach for item response function estimation to detect item misfit

    Köhler, C., Robitzsch, A., Fährmann, K., von Davier, M. & Hartig, J., 07.2021, In: British Journal of Mathematical and Statistical Psychology. 74, S1, p. 157-175 19 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. About the equivalence of the latent D-scoring model and the two-parameter logistic item response model

    Robitzsch, A., 22.06.2021, In: Mathematics. 9, 13, 17 p., 1465.

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. Causal inference with multilevel data: A comparison of different propensity score weighting approaches

    Fuentes, A., Lüdtke, O. & Robitzsch, A., 15.06.2021, (E-pub ahead of print) In: Multivariate Behavioral Research.

    Research output: Contribution to journalJournal articleResearchpeer-review

  5. A comparison of estimation methods for the Rasch model

    Robitzsch, A., 06.2021, Book of short papers: SIS 2021. Perna, C., Salvati, N. & Schirripa Spagnolo, F. (eds.). Pearson, p. 157-162

    Research output: Chapter in anthology/conference proceedingContribution to collected edition/anthologyResearchpeer-review

  6. Validating theoretical assumptions about reading with cognitive diagnosis models

    George, A. C. & Robitzsch, A., 06.2021, In: International Journal of Testing. 21, 2, p. 105-129 25 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  7. A note on a computationally efficient implementation of the EM algorithm in item response models

    Robitzsch, A., 11.05.2021, In: Quantitative and Computational Methods in Behavioral Sciences. 1, 1, 16 p., e3783.

    Research output: Contribution to journalJournal articleResearchpeer-review

  8. A comparison of penalized maximum likelihood estimation and Markov Chain Monte Carlo techniques for estimating confirmatory factor analysis models with small sample sizes

    Lüdtke, O., Ulitzsch, E. & Robitzsch, A., 29.04.2021, In: Frontiers in Psychology. 12, 25 p., 615162.

    Research output: Contribution to journalJournal articleResearchpeer-review

  9. A Bayesian item response model for examining item position effects in complex survey data

    Trendtel, M. & Robitzsch, A., 02.2021, In: Journal of Educational and Behavioral Statistics. 46, 1, p. 34-57

    Research output: Contribution to journalJournal articleResearchpeer-review

  10. On the performance of Bayesian approaches in small samples: A comment on Smid, McNeish, Miocevic, and van de Schoot (2020)

    Zitzmann, S., Lüdtke, O., Robitzsch, A. & Hecht, M., 02.01.2021, In: Structural Equation Modeling: A Multidisciplinary Journal. 28, 1, p. 40-50 11 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  11. 2020
  12. Leistungsveränderungen in TIMSS zwischen 2015 und 2019: Die Rolle des Testmediums und des methodischen Vorgehens bei der Trendschätzung

    Robitzsch, A., Lüdtke, O., Schwippert, K., Goldhammer, F., Kröhne, U. & Köller, O., 12.2020, TIMSS 2019: Mathematische und naturwissenschaftliche Kompetenzen von Grundschulkindern in Deutschland im internationalen Vergleich. Schwippert, K., Kasper, D., Köller, O., McElvany, N., Selter, C., Steffensky, M. & Wendt, H. (eds.). Münster: Waxmann, p. 169-186

    Research output: Chapter in anthology/conference proceedingContribution to collected edition/anthologyResearch

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