For a more comprehensive list, see Google Scholar.

• Sühr, T., Dorner, F. E., Salaudeen, O., Kelava, A., & Samadi, S. (2025). Stop evaluating AI with human tests, develop principled, AI-specific tests instead. arXiv preprint arXiv:2507.23009. https://arxiv.org/abs/2507.23009
• Sühr, T., Dorner, F. E., Samadi, S., & Kelava, A. (2025). Challenging the validity of personality tests for large language models. In Proceedings of the 5th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO ’25) (pp. 74–81). Association for Computing Machinery. https://doi.org/10.1145/3757887.3763016
• Andriamiarana, V., Kilian, P., Brandt, H., & Kelava, A. (2025). Are Bayesian regularization methods a must for multilevel dynamic latent variables models? Behavior Research Methods, 57(2), 71. https://doi.org/10.3758/s13428-024-02589-9
• Noventa, S., Heller, J., Ye, S., & Kelava, A. (2025). Toward a unified perspective on assessment models, part II: Dichotomous latent variables. Journal of Mathematical Psychology, 125, 10292. https://doi.org/10.1016/j.jmp.2025.102926
• Noventa, S., Ye, S., Kelava, A., & Spoto, A. (2024). On the identifiability of 3-and 4-parameter item response theory models from the perspective of knowledge space theory. Psychometrika, 89(2), 486-516. https://doi.org/10.1007/s11336-023-09912-5
• Nagel, M., Fischer, L., Pawlowski, T., & Kelava, A. (2024). An alternative prior for estimation in high-dimensional settings. Structural Equation Modeling: A Multidisciplinary Journal, 31(6), 939–951. https://doi.org/10.1080/10705511.2024.2291234
• Noventa, S., Heller, J., & Kelava, A. (2024). Toward a unified perspective on assessment models, part I: Foundations of a framework. Journal of Mathematical Psychology, 122, 102872. Elsevier. https://doi.org/10.1016/j.jmp.2024.102872
• Noventa, S., Faleh, R., & Kelava, A. (2024). On an EM-based closed-form solution for 2 parameter IRT models. arXiv preprint, arXiv:2411.18351. https://doi.org/10.48550/arXiv.2411.18351
• Fischer, L., Nagel, M., Kelava, A., & Pawlowski, T. (2024). Emotional drinking: Surprise, suspense, and alcohol use during soccer matches. Preprint. (July 31, 2024). Available at SSRN: https://ssrn.com/abstract=4912703
• Sühr, T., Dorner, F. E., Samadi, S., & Kelava, A. (2023). Challenging the validity of personality tests for large language models. arXiv preprint, arXiv:2311.18351. https://arxiv.org/abs/2311.05297
• Wägerle, D., & Kelava, A. (2023). Investigating evidence, key concepts, and research gaps on social inequalities in the postdoctoral phase within German higher education: A scoping review protocol. Open Science Framework (OSF) Preprint. https://doi.org/10.31219/osf.io/abcd1
• Dorner, F. E., Sühr, T., Samadi, S., & Kelava, A. (2023). Do personality tests generalize to Large Language Models? Socially Responsible Language Modelling Research (SoLaR) 2023 Workshop at NeurIPS 2023. https://arxiv.org/abs/2311.05297
• Kilian, P., Leyhr, D., Urban, C. J., Höner, O., & Kelava, A. (2023). A deep learning factor analysis model based on importance-weighted variational inference and normalizing flow priors: Evaluation within a set of multidimensional performance assessments in youth elite soccer players. Statistical Analysis and Data Mining, 16(5), 474-487. Link
• Andriamiarana, V., Kilian, P., Kelava, A., & Brandt, H. (2023). On the requirements of non-linear dynamic latent class SEM: A simulation study with varying numbers of subjects and time points. Structural Equation Modeling, 30(5), 789-806. Link
• Kilian, P., Ye, S., & Kelava, A. (2023). Mixed effects in machine learning - A flexible mixedML framework to add random effects to supervised machine learning regression. Transactions on Machine Learning Research (TMLR).Link
• Merk, S., Groß Ophoff, J., & Kelava, A. (2023). Rich data, poor information? Teachers’ perceptions of mean differences in graphical feedback from statewide tests. Learning and Instruction, 84, 101717. Link
• Kelava, A., Kilian, P., Glaesser, J., Merk, S., & Brandt, H. (2022). Forecasting intraindividual changes of affective states taking into account interindividual differences using intensive longitudinal data from a university student drop out study in math. Psychometrika, 87(2), 533-558. Link
• Schneider, J., Rosman, T., Kelava, A., & Merk, S. (2022). Do Open Science Badges increase trust in scientists among undergraduates, scientists, and the public? Psychological Science, 33(9), 1588-1604. Link
• Kilian, P., Loose, F., & Kelava, A. (2020). Predicting math student success in the initial phase of college with sparse information using approaches from statistical learning. Frontiers in Education, 5. Link
• Brandt, H., Umbach, N., Kelava, A., & Bollen, K. (2020). Comparing estimators for latent interaction models under structural and distributional misspecifications. Psychological Methods. Link
• Kelava, A. & Brandt, H. (2019). A Nonlinear Dynamic Latent Class Structural Equation Model. Structural Equation Modeling, 26,509-528. Link
• Noventa, S., Spoto, A., Heller, J., & Kelava, A. (2019). On a generalization of local independence in item response theory based on knowledge space theory. Psychometrika, 84, 395-421. Link
• Graser, J., Heimlich, C., Kelava, A., Hofmann, S.G., Stangier, U., & Schreiber, F. (2019). Erfassung der Emotionsregulation bei Jugendlichen anhand des „Affective Style Questionnaire (ASQ-Y)“ . [Assessment of emotion regulation strategies of youth using the Affective Style Questionnaire (ASQ-Y).] Diagnostica, 65, 49-59. Link
• Leyhr, D., Raabe, J., Schultz, F., Kelava, A., & Höner, O. (2019). The adolescent motor performance development of elite female soccer players: A study of prognostic relevance for future success in adulthood using multilevel modelling. Journal of Sports Sciences, 1-10. Link
• Brandt, H., Cambria, J., & Kelava, A. (2018). An adaptive Bayesian lasso approach with spike-and-slab priors to identify linear and interaction effects in structural equation models. Structural Equation Modeling, 25, 956-960. Link
• Gemein, C., Roos, M., Wolf, A., Hermann, N., Kelava, A., Chasan, R., Weipert, K., Helmig, I., Bogossian, H., Hamm, C.W., Neumann, T., Schmitt, J., & Erkapic, D. (2018). Tilt testing and what you should know about it – Experience with 835 consecutive patients with syncope of unknown origin. International Journal of Cardiology, 258, 90–96. Link