Pascal Kieslich

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I am a Senior Principal Data Scientist at the healthcare business of Merck KGaA, Darmstadt, Germany. Before joining Merck, I received a doctorate in Psychology and worked as a postdoctoral researcher at the University of Mannheim with a focus on methodology, process tracing, and human decision making.

Selected open-source software packages

mousetrap: R package for processing, analyzing, clustering, and visualizing mouse-tracking data

readbulk: R package for reading and combining multiple data files

mousetrap-os: Python package for implementing mouse-tracking in OpenSesame

psynteract-os: Python package for real-time interactive experiments in OpenSesame

Overview of software and open-source code (on GitHub)

Selected publications

Manitz, J., Gerhold-Ay, A., Kieslich, P., Shah, P., Mrowiec, T., & Tyroller, K. (2024). Avelumab first-line maintenance in advanced urothelial carcinoma: Complete screening for prognostic and predictive factors using machine learning in the JAVELIN Bladder 100 phase 3 trial. Cancer Medicine, 13(12), e7411. https://doi.org/10.1002/cam4.7411 (PDF)

Leipold, F. M., Kieslich, P. J., Henninger, F., Fernández-Fontelo, A., Greven, S., & Kreuter, F. (2024). Detecting respondent burden in online surveys: How different sources of question difficulty influence cursor movements. Social Science Computer Review, 08944393241247425. https://doi.org/10.1177/08944393241247425 (PDF) (preregistration) (data & analyses)

Tiede, K. E., Henninger, F., & Kieslich, P. J. (2022). Revisiting the Open Sampling format: Improving risky choices through a novel graphical representation. Psychonomic Bulletin & Review, 29, 648-659. https://doi.org/10.3758/s13423-021-02018-4 (PDF) (preregistration study 2b) (preregistration study 3) (data & analyses)

Henninger, F., Shevchenko, Y., Mertens, U. K., Kieslich, P. J., & Hilbig, B. E. (2022). lab.js: A free, open, online study builder. Behavior Research Methods, 54, 556–573. https://doi.org/10.3758/s13428-019-01283-5 (PDF) (software) (source code)

Kieslich, P. J., Schoemann, M., Grage, T., Hepp, J., & Scherbaum, S. (2020). Design factors in mouse-tracking: What makes a difference? Behavior Research Methods, 52(1), 317-341. https://doi.org/10.3758/s13428-019-01228-y (PDF) (data & analyses)

Kieslich, P. J., Henninger, F., Wulff, D. U., Haslbeck, J. M. B., & Schulte-Mecklenbeck, M. (2019). Mouse-tracking: A practical guide to implementation and analysis. In M. Schulte-Mecklenbeck, A. Kühberger, & J. G. Johnson (Eds.), A Handbook of Process Tracing Methods (pp. 111-130). New York: Routledge. https://doi.org/10.4324/9781315160559-9 (preprint) (software) (analyses)

Aczel, B., Szollosi, A., Palfi, B., Szaszi, B., & Kieslich, P. J. (2018). Is action execution part of the decision-making process? An investigation of the embodied choice hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(6), 918-926. https://doi.org/10.1037/xlm0000484 (data & analyses)

Heck, D. W., Erdfelder, E., & Kieslich, P. J. (2018). Generalized processing tree models: Jointly modeling discrete and continuous variables. Psychometrika, 83(4), 893-918. https://doi.org/10.1007/s11336-018-9622-0 (data & analyses)

Hepp, J., Störkel, L., Kieslich, P. J., Schmahl, C., & Niedtfeld, I. (2018). Negative evaluation of individuals with borderline personality disorder at zero acquaintance. Behaviour Research and Therapy, 111, 84-91. https://doi.org/10.1016/j.brat.2018.09.009 (data)

Bröder, A., Gräf, M., & Kieslich, P. J. (2017). Measuring the relative contributions of rule-based and exemplar-based processes in judgment: Validation of a simple model. Judgment and Decision Making, 12(5), 491-506. https://doi.org/10.1017/S1930297500006513 (PDF) (data) (simulations)

Kieslich, P. J., & Henninger, F. (2017). Mousetrap: An integrated, open-source mouse-tracking package. Behavior Research Methods, 49(5), 1652-1667. https://doi.org/10.3758/s13428-017-0900-z (PDF) (software) (data & analyses)

Kieslich, P. J., & Hilbig, B. E. (2014). Cognitive conflict in social dilemmas: An analysis of response dynamics. Judgment and Decision Making, 9(6), 510-522. https://doi.org/10.1017/S1930297500006392 (PDF) (data) (analyses)

Overview of publications (on Google Scholar)