1. 2022
  2. Mean comparisons of many groups in the presence of DIF: An evaluation of linking and concurrent scaling approaches

    Robitzsch, A. & Lüdtke, O., 02.2022, In: Journal of Educational and Behavioral Statistics. 47, 1, p. 36-68

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. 2021
  4. Analyzing longitudinal social relations model data using the social relations structural equation model

    Nestler, S., Lüdtke, O. & Robitzsch, A., 14.12.2021, (E-pub ahead of print) In: Journal of Educational and Behavioral Statistics.

    Research output: Contribution to journalJournal articleResearchpeer-review

  5. On the treatment of missing item responses in educational large-scale assessment data: An illustrative simulation study and a case study using PISA 2018 mathematics data

    Robitzsch, A., 14.12.2021, In: European Journal of Investigation in Health, Psychology and Education. 11, 4, p. 1653-1687 35 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  6. Cognitively diagnostic analysis using the G-DINA model in R

    Shi, Q., Ma, W., Robitzsch, A., Sorrel, M. A. & Man, K., 08.12.2021, In: Psych. 3, 4, p. 812-835 24 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  7. 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

  8. Multiple imputation of missing data in multilevel models with the R package mdmb: A flexible sequential modeling approach

    Grund, S., Lüdtke, O. & Robitzsch, A., 12.2021, In: Behavior Research Methods. 53, 6, p. 2631-2649 19 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  9. A comprehensive simulation study of estimation methods for the Rasch model

    Robitzsch, A., 01.10.2021, In: Stats. 4, 4, p. 814-836 23 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  10. A continuous HYBRID IRT model for modeling changes in guessing behavior in proficiency tests

    Nagy, G. & Robitzsch, A., 30.09.2021, In: Psychological Test and Assessment Modeling. 63, 3, p. 361-395 35 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  11. A comparison of linking methods for two groups for the two-parameter logistic item response model in the presence and absence of random differential item functioning

    Robitzsch, A., 15.09.2021, In: Foundations. 1, 1, p. 116-144

    Research output: Contribution to journalJournal articleResearchpeer-review

  12. On the treatment of missing data in background questionnaires in educational large-scale assessments: An evaluation of different procedures

    Grund, S., Lüdtke, O. & Robitzsch, A., 08.2021, In: Journal of Educational and Behavioral Statistics. 46, 4, p. 430-465 36 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  13. Item parameter estimation in multistage designs: A comparison of different estimation approaches for the Rasch model

    Steinfeld, J. & Robitzsch, A., 08.07.2021, In: Psych. 3, 3, p. 279-307 29 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  14. 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

  15. 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

  16. 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

  17. A comparison of estimation methods for the Rasch model

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

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

  18. 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

  19. 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

  20. 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

  21. 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

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