Debelak, R., & Strobl, C. (2024). Violations of unidimensionality and differential item functioning. In S. Greiff, K. Schweizer, & S. Troche (Eds.), Method effects in the psychological measurement. Hogrefe.
Zimmer, F., Henninger, M., & Debelak, R. (2023). Sample size planning for complex study designs: A tutorial for the mlpwr package. Behavior Research Methods.
[bib] [url]
Zimmer, F., Draxler, C., & Debelak, R. (2023). Power analysis for the Wald, LR, score, and gradient tests in a marginal maximum likelihood framework: Applications in IRT. Psychometrika, 88, 1249–1298.
[bib] [doi:10.1007/s11336-022-09883-5] [url]
Henninger, M., Debelak, R., & Strobl, C. (2023). A new stopping criterion for Rasch trees based on the Mantel-Haenszel effect size measure for differential item functioning. Educational and Psychological Measurement, 83(1), 181–212.
[bib] [doi:10.1177/00131644221077135] [url]
Debelak, R., Appelbaum, S., Debeer, D., & Tomasik, M. J. (2023). Detecting differential item functioning in 2PL multistage assessments. Psych, 5(2), 461–477.
[bib] [doi:10.3390/psych5020031] [url]
Henninger, M., Debelak, R., Rothacher, Y., & Strobl, C. (2023). Interpretable machine learning for psychological research: Opportunities and pitfalls. Psychological Methods.
[bib] [doi:10.1037/met0000560] [url]
Debelak, R., & Driver, C. C. (2023). Score-based measurement invariance checks for large-scale assessments. PsyArXiv.
[bib] [doi:10.31234/] [url]
Zimmer, F., & Debelak, R. (2023). Simulation-based design optimization for statistical power: Utilizing machine learning. Psychological Methods.
[bib] [doi:10.1037/met0000611] [url]
Fellinghauer, C., Debelak, R., & Strobl, C. (2023). What Affects the Quality of Score Transformations? Potential issues in True-Score Equating using the Partial Credit model. Educational and Psychological Measurement, 83(6), 1249–1290.
[bib] [doi:10.1177/00131644221143051] [url]
Debelak, R., & Urban, C. J. (2022). An evaluation of deep learning approaches for factor analysis of response and response time data. PsyArXiv.
[bib] [doi:10.31234/]
Debelak, R., Strobl, C., & Zeigenfuse, M. D. (2022). An introduction to the Rasch model with examples in R (p. 322). Chapman & Hall/CRC.
[bib] [doi:10.1201/9781315200620] [url]
Schneider, L., Strobl, C., Zeileis, A., & Debelak, R. (2022). An R toolbox for score-based measurement invariance tests in IRT models. Behavior Research Methods, 54, 2101–2113.
[bib] [doi:10.3758/s13428-021-01689-0] [url]
Becker, M. O., Dobrota, R., Garaiman, A., Debelak, R., Fligelstone, K., Kennedy, A. T., Roennow, A., Allanore, Y., Carreira, P. E., Czirják, L.others. (2022). Development and validation of a patient-reported outcome measure for systemic sclerosis: The EULAR systemic sclerosis impact of disease (ScleroID) questionnaire. Annals of the Rheumatic Diseases, 81(4), 507–515.
[bib] [doi:10.1136/annrheumdis-2021-220702]
Castro, R. P., Haug, S., Debelak, R., Jakob, R., Kowatsch, T., Schaub, M. P.others. (2022). Engagement with a mobile phone–based life skills intervention for adolescents and its association with participant characteristics and outcomes: Tree-Based analysis. Journal of Medical Internet Research, 24(1), e28638.
[bib] [doi:10.2196/28638]
Zimmer, F., & Debelak, R. (2022). irtpwr: Power analysis for IRT models using the Wald, LR, Score, and Gradient statistics.
[bib] [url]
Zimmer, F., & Debelak, R. (2022). mlpwr: A power analysis toolbox to find cost-efficient study designs.
[bib] [url]
Zeileis, A., Strobl, C., Wickelmaier, F., Komboz, B., Kopf, J., Schneider, L., & Debelak, R. (2022). psychotools: Infrastructure for psychometric modeling.
[bib] [url]
Zeileis, A., Strobl, C., Wickelmaier, F., Komboz, B., Kopf, J., Dreifuss, D., & Debelak, R. (2022). psychotree: Recursive partitioning based on psychometric models.
[bib] [url]
Debelak, R., Pawel, S., Strobl, C., & Merkle, E. C. (2022). Score-based measurement invariance checks for Bayesian maximum-a-posteriori estimates in item response theory. British Journal of Mathematical and Statistical Psychology, 75(3), 728–752.
[bib] [doi:10.1111/bmsp.12275] [url]
Debelak, R., & Debeer, D. (2021). An evaluation of DIF tests in multistage tests for continuous covariates. Psych, 3(4), 619–639.
[bib] [doi:10.3390/psych3040040] [url]
Mair, P., Hatzinger, R., Maier, M. J., & Rudolf Debelak als Contributor. (2021). eRm: Extended Rasch modeling. 1.0-0.
[bib] [url]
Walther, A., Grub, J., Ehlert, U., Wehrli, S., Rice, S., Seidler, Z. E., & Debelak, R. (2021). Male depression risk, psychological distress, and psychotherapy uptake: Validation of the german version of the male depression risk scale. Journal of Affective Disorders Reports, 4, 100107.
[bib] [doi:10.1016/j.jadr.2021.100107] [url]
Luo, M., Debelak, R., Schneider, G., Martin, M., & Demiray, B. (2021). With a little help from familiar interlocutors: Real-world language use in young and older adults. Aging & Mental Health, 25(12), 2310–2319.
[bib] [doi:10.1080/13607863.2020.1822288]
Gloor, J., Strobl, C., & Debelak, R. (2020). DSI Insights: Wege aus der Angst vor Algorithmen. Inside IT Kolumne. Inside IT Kolumne.
[bib] [url]
Debelak, R., Debeer, D., Applebaum, S., & Gierl, M. J. (2020). mstDIF: A collection of DIF tests for multistage tests.
[bib] [url]
Huelmann, T., Debelak, R., & Strobl, C. (2019). A comparison of aggregation rules for selecting anchor items in multi group DIF analysis. Journal of Educational Measurement, 57(2), 185–215.
[bib] [doi:10.1111/jedm.12246]
Debelak, R. (2019). An evaluation of overall goodness-of-fit tests for the Rasch model. Frontiers in Psychology, 9, 2710.
[bib] [doi:10.3389/fpsyg.2018.02710]
Debelak, R., & Strobl, C. (2019). Investigating measurement invariance by means of parameter instability tests for 2PL and 3PL models. Educational and Psychological Measurement, 79(2), 385–398.
[bib] [doi:10.1177/0013164418777784]
Schneider, L., Chalmers, R. P., Debelak, R., & Merkle, E. C. (2019). Model selection of nested and non-nested item response models using Vuong tests. Multivariate Behavioral Research.
[bib] [doi:10.1080/00273171.2019.1664280]
Debelak, R., & Koller, I. (2019). Testing the local independence assumption of the rasch model with Q3-based nonparametric model tests. Applied Psychological Measurement, 44(2), 103–117.
[bib] [doi:10.1177/0146621619835501]
Vetter, M., Schünemann, A. L., Brieber, D., Debelak, R., Gatscha, M., Grünsteidel, F., Herle, M., Mandler, G., & Ortner, T. M. (2018). Cognitive and personality determinants of safe driving performance in professional drivers. Transportation Research Part F: Traffic Psychology and Behaviour, 52, 191–201.
[bib] [doi:10.1016/j.trf.2017.11.008]
Bollmann, S., Cook, D., Dumas, J., Fox, J., Josse, J., Keyes, O., Strobl, C., Turner, H., & Debelak, R. (2017). A first survey on the diversity of the R community. The R Journal, 9(2), 541–552.
[bib] [url]
Walther, A., Mahler, F., Debelak, R., & Ehlert, U. (2017). Psychobiological protective factors modifying the association between age and sexual health in men: Findings from the men’s health 40+ study. American Journal of Men’s Health, 11(3), 737–747.
[bib] [doi:10.1177/1557988316689238]
Kaller, C. P., Debelak, R., Köstering, L., Egle, J., Rahm, B., Wild, P. S., Blettner, M., Beutel, M. E., & Unterrainer, J. M. (2016). Assessing planning ability across the adult life span: Population-representative and age-adjusted reliability estimates for the tower of london (TOL-F). Archives of Clinical Neuropsychology, 31(2), 148–164.
[bib] [doi:10.1093/arclin/acv088]
Debelak, R., Egle, J., Köstering, L., & Kaller, C. P. (2016). Assessment of planning ability: Psychometric analyses on the unidimensionality and construct validity of the tower of london task (TOL-F). Neuropsychology, 30(3), 346–360.
[bib] [doi:10.1037/neu0000238]
Debelak, R., & Tran, U. S. (2016). Comparing the effects of different smoothing algorithms on the assessment of dimensionality of ordered categorical items with parallel analysis. PLoS ONE, 11(2), e0148143.
[bib] [doi:10.1371/journal.pone.0148143]
Vetter, M., Schünemann, L., Debelak, R., Gatscha, M., Herle, M., Mandler, G., & Ortner, T. M. (2015). Vorhersage von sicherheitsrelevantem Fahrverhalten bei Berufskraftfahrern: eine theoriegeleitete Validierung von Leistungs- und Persönlichkeitstests. Zeitschrift für Verkehrssicherheit, 61, 222--234.
Gmehlin, D., Fuermaier, A. B., Walther, S., Debelak, R., Rentrop, M., Westermann, C., Sharma, A., Tucha, L., Koerts, J., Tucha, O.others. (2014). Intraindividual variability in inhibitory function in adults with ADHD – an ex-gaussian approach. PLoS ONE, 9(12), e112298.
[bib] [doi:10.1371/journal.pone.0112298]
Debelak, R., Gittler, G., & Arendasy, M. (2014). On gender differences in mental rotation processing speed. Learning and Individual Differences, 29, 8–17.
[bib] [doi:10.1016/j.lindif.2013.10.003]
Debelak, R., & Tran, U. S. (2013). Principal component analysis of smoothed correlation matrices as a measure of dimensionality. Educational and Psychological Measurement, 73, 63–77.
[bib] [doi:10.1177/0013164412457366]
Debelak, R., & Arendasy, M. (2012). An algorithm for clustering items and testing unidimensionality in Rasch measurement. Educational and Psychological Measurement, 72(3), 375–387.
[bib] [doi:10.1177/0013164411426005]
Rodewald, K., Bartolovic, M., Debelak, R., Aschenbrenner, S., Weisbrod, M., & Roesch-Ely, D. (2012). Eine Normierungsstudie eines modifizierten Trail Making Tests im deutschsprachigen Raum. Zeitschrift für Neuropsychologie, 23, 37–48.
[bib] [doi:10.1024/1016-264X/a000060]