1. 2022
  2. Book review: Computational Psychometrics: New methodologies for a new generation of digital learning and assessment

    Ulitzsch, E., 12.2022, In: Psychometrika. 87, 4, p. 1571-1574

    Research output: Contribution to journalCritical reviewResearch

  3. An explanatory mixture IRT model for careless and insufficient effort responding in self-report measures

    Ulitzsch, E., Yildirim-Erbasli, S. N., Gorgun, G. & Bulut, O., 11.2022, In: British Journal of Mathematical and Statistical Psychology. 75, 3, p. 668-698

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. The role of rapid guessing and test‐taking persistence in modelling test‐taking engagement

    Nagy, G., Ulitzsch, E. & Lindner, M. A., 08.2022, (E-pub ahead of print) In: Journal of Computer Assisted Learning. 16 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  5. A machine learning-based procedure for leveraging clickstream data to investigate early predictability of failure on interactive tasks

    Ulitzsch, E., Ulitzsch, V., He, Q. & Lüdtke, O., 01.06.2022, (E-pub ahead of print) In: Behavior Research Methods. 14 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  6. A response-time-based latent response mixture model for identifying and modeling careless and insufficient effort responding in survey data

    Ulitzsch, E., Pohl, S., Khorramdel, L., Kroehne, U. & von Davier, M., 06.2022, In: Psychometrika. 87, 2, p. 593-619 27 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  7. A Bayesian approach to estimating reciprocal effects with the bivariate STARTS model

    Lüdtke, O., Robitzsch, A. & Ulitzsch, E., 03.2022, (E-pub ahead of print) In: Multivariate Behavioral Research.

    Research output: Contribution to journalJournal articleResearchpeer-review

  8. Evaluating Stan's variational Bayes algorithm for estimating multidimensional IRT models

    Ulitzsch, E. & Nestler, S., 05.02.2022, In: Psych. 4, 1, p. 73-88

    Research output: Contribution to journalJournal articleResearchpeer-review

  9. Using sequence mining techniques for understanding incorrect behavioral patterns on interactive tasks

    Ulitzsch, E., He, Q. & Pohl, S., 02.2022, In: Journal of Educational and Behavioral Statistics. 47, 1, p. 3-35

    Research output: Contribution to journalJournal articleResearchpeer-review

  10. 2021
  11. Alleviating estimation problems in small sample structural equation modeling: A comparison of constrained maximum likelihood, Bayesian estimation, and fixed reliability approaches

    Ulitzsch, E., Lüdtke, O. & Robitzsch, A., 12.2021, (E-pub ahead of print) In: Psychological Methods.

    Research output: Contribution to journalJournal articleResearchpeer-review

  12. A multilevel mixture IRT framework for modeling response times as predictors or indicators of response engagement in IRT models

    Nagy, G. & Ulitzsch, E., 13.09.2021, (E-pub ahead of print) In: Educational and Psychological Measurement. 35 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

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