I am a PhD candidate at the Methodology and Statistics department of Utrecht University. My main research interests are privacy-preserving statistics (including synthetic data) and Bayesian methods for data analysis. I developed an R-package densityratio for density ratio estimation, and contribute to the open source software packages mice and JASP. Besides, I teach statistics and data science courses to Bachelor and Master students.
For an extensive overview of my education and work experience, please see my cv.
Education
| 2022 | MSc. Methodology and Statistics cum laude |
| 2022 | MSc. Sociology and Social Research cum laude |
| 2019 | Liberal Arts & Sciences |
Selected publications
| Klugkist, I., & Volker, T. B. (2023). Bayesian evidence synthesis for informative hypotheses: An introduction. Psychological Methods. Advance online publication. (link) |
| Volker, T. B., de Wolf, P. P., & van Kesteren, E. J. (2024). A density ratio framework for evaluating the utility of synthetic data. arXiv:2408.13167. (link) |
| Volker, T. B., & Vink, G. (2021). Anonymiced shareable data: Using mice to create and analyze multiply imputed synthetic datasets. Psych, 3(4), 703-716. (*link) |