Publikationen
Angelike, T., & Heck, D. W. (2026). Evaluating large language models for feature extraction from verbal stimuli: A simulation-based workflow. PsyArXiv. https://osf.io/preprints/psyarxiv/xphm9_v1/ [under review]
Angelike, T., & Reips, U.-D. (2026). Measurement error is lower for visual analogue scales than for slider scales. Behavior Research Methods, 58, 244. https://doi.org/10.3758/s13428-026-03108-8
Papenberg, M., & Angelike, T. (2026). A simulation-based comparison of minimization, rerandomization, and anticlustering for creating experimental conditions. Methodology. https://doi.org/10.5964/meth.17973
Angelike, T., Funke, F., & Reips, U.-D. (2025). Reducing measurement error by tackling formatting error: Theoretical and empirical evidence for high data quality with visual analogue scales [under review]
Angelike, T., & Musch, J. (2025). A comparison of algorithmic complexity and entropy for the detection of patterns in short human-generated random sequences [under review]
Angelike, T., Diedenhofen, D., & Musch, J. (2025). An experimental validation of an axiomatically derived scoring rule for the assessment of partial knowledge [under review]
Angelike, T., & Papenberg, M. (2025). Problems when using anticlustering for the partitioning of cross-validation folds. OSF. https://osf.io/preprints/osf/b5fus_v1 [under review]
Angelike, T., & Musch, J. (2025). An improved modeling approach to investigate biases in human random number generation. PLOS ONE, 20(5), e0324870. https://doi.org/10.1371/journal.pone.0324870
Angelike, T., & Musch, J. (2024). A comparative evaluation of measures to assess randomness in human-generated sequences. Behavior Research Methods, 56(7), 7831-7848. https://doi.org/10.3758/s13428-024-02456-7
Vorträge
Reips, U.-D., & Angelike, T. (2025). Visual analogue scales versus slider scales: Measurement error. Talk at the Society for Computation in Psychology (SCiP) during the Psychonomic Society 66th Annual Meeting, Denver (USA).
Angelike, T., & Reips, U.-D. (2025). Theoretical and empirical evidence for high data quality with visual analogue scales. Talk at the 67th meeting of Experimental Psychologists (TeaP), Frankfurt.
Angelike, T. (2024). Methods for measuring and modelling randomness in human generated number sequences. Invited Talk at department for Research Methods, Assessment, and iScience, Universität Konstanz.
Angelike, T., & Musch, J. (2024). An improved modeling approach to investigate biases in human random number generation. Talk at the 66th meeting of Experimental Psychologists (TeaP), Regensburg.
Angelike, T., Diedenhofen, B., & Musch, J. (2023). Experimental Validation of a New Axiomatically Derived Scoring Rule for the Subset Selection Response Format. Talk at the Society for Computation in Psychology (SCiP) during the Psychonomic Society 64th Annual Meeting, San Francisco (USA).
