Hanne Oberman

Statistician, interdisciplinarian, open scientist

I am very passionate about ‘dull’ or ‘difficult’ topics such as statistics, programming, and philosophy of science. I’m motivated to use my enthusiasm and expertise to improve the quality of academic research and education. I aspire to (help others to) solve complex real-world problems that require insights from many disciplines and methodologies.

Experience

2024-permanent

2023-current

2020-2023

Education

2023-current

2018-2020

2018

2014-2018

Ancillary positions

2022-current

2022-current
  • Faculty Open Science Team FOST member, chair since 2024 | Utrecht University | Utrecht | The Netherlands

2021, 2023

2019-2020

2017-2020

2017-2022
  • Representative in advisory bodies, e.g. student council Liberal Arts and Sciences | Utrecht University | Utrecht | The Netherlands

2016-2017
  • Research internship with Merel van Goch | Utrecht University | Utrecht | The Netherlands

2014-2018
  • Board member and committees for study association USLAS Atlas | Utrecht University | Utrecht | The Netherlands

Grants and awards

2023
  • Project, ‘MICE ONLINE: A new service to solve missing data problems’, Open Science Fund, Utrecht University, Utrecht, The Netherlands

2022
  • Project, ‘dessert: an automated tool for transparent and reproducible scientific reporting’, Open Science Fund , Utrecht University, Utrecht, The Netherlands

2019
  • Best poster, ‘Will You Publish Null Papers?’, Social and Behavioural Sciences Graduate Poster Fair, Utrecht University, Utrecht, The Netherlands

2018
  • Fellowship award, Global Academy of Liberal Arts Annual Conference ‘Creativity and the Liberal Arts’ (HUMA 887), Concordia University, Montréal, Canada

Professional memberships and service

Publications

Oberman, H. (2024). Measuring Open Science. https://doi.org/10.53962/tn38-4q91
Oberman, H. I., & Vink, G. (2024). Toward a standardized evaluation of imputation methodology. Biometrical Journal, 66(1), 2200107. https://doi.org/10.1002/bimj.202200107
Oberman, H., van Harten, V., Rozsos, T., & Peeters, S. (2024). CODECHECK certificate 2024-021. https://doi.org/10.5281/zenodo.14261193
Snel, E., Engbersen, G., de Boom, J., van de Heijden, P., & Oberman, H. (2024). Ongelijke verdeling van de sociale gevolgen van de coronapandemie. Erasmus Universiteit/Risbo.
Vink, G., Volker, T. B., Oberman, H. I., Shehwana, H., Cai, M., & Van Buuren, S. (2024). A series of instructional vignettes for mice in R with applications to real and synthetic data. Zenodo. https://doi.org/10.5281/zenodo.12586939
Liu, D., Oberman, H. I., Muñoz, J., Hoogland, J., & Debray, T. P. A. (2023). Quality Control, Data Cleaning, Imputation. In F. W. Asselbergs, S. Denaxas, D. L. Oberski, & J. H. Moore (Eds.), Clinical Applications of Artificial Intelligence in Real-World Data (pp. 7–36). Springer International Publishing. https://doi.org/10.1007/978-3-031-36678-9_2
Snel, E., Engbersen, G., Van Der Heijden, P., & Oberman, H. (2023). Een longitudinale studie naar het afgenomen vertrouwen gedurende de coronapandemie. Mens & Maatschappij, 98(4), 369–394. https://doi.org/10.5117/MEM2023.4.004.SNEL
van Veelen, R., de Haan, J., Oberman, H., Vink, P., & Nelson, J. (2023). Open Science Monitor 2022. Zenodo. https://doi.org/10.5281/zenodo.8375726
Oberman, H. I. (2022). Ggmice: Visualizations for ’mice’ with ’Ggplot2’. Zenodo. https://doi.org/10.5281/zenodo.6532702
Oberman, H. I. (2021). Visualizing uncertainty due to missing data. IEEE VIS, VisComm Track. https://doi.org/10.31219/osf.io/ahtfy
Oberman, H. I., Bakker, M., Nguyen, D., & Oberski, D. (2021). Preregistration of data science studies. Open Science Festival. https://doi.org/10.17605/OSF.IO/Y6J73
Oberman, H. I., van Buuren, S., & Vink, G. (2021). Missing the Point: Non-Convergence in Iterative Imputation Algorithms. https://arxiv.org/abs/2110.11951
Oberman, H. I., Nijman, S. W. J., Vink, G., Debray, T. P. A., & Smeden, M. van. (n.d.). Real-time handling of missing data in the application of prediction models: A comparison of methods.



Teaching and supervision

I am passionate about teaching and in the process of obtaining a university teaching qualification (‘BKO’). I enjoy teaching a wide range of topics, from introductory statistics to advanced data science, and from qualitative research methodology to missing data methodology.

Thesis supervision

2023-current
  • Research Master thesis Methodology and Statistics for the Behavioural, Biomedical and Social Sciences, co-supervision of 1 student (2023-2024, 2024-2025)

2020-2022
  • Master thesis Applied Data Science ‘Research Project GSNS’, co-supervision of 3 students (2020-2021), supervision of 3 students (2021-2022)

Missing data methodology

2021-current
  • ‘Missing Data and Causal Effects’ (advanced undergraduate), lectures (2023-2024, 2024-2025), work groups and grading (2021-2022, 2022-2023, 2024-2025)

Programming and applied data science

2024-2025
  • ‘Data Wrangling and Data Analysis’ (academic master), supervising practicals and grading (2024-2025)

2022-current
  • ‘Statistical Programming with R’ (summer school), guest lecture (2022-2023, 2023-2024)

2021-current
  • ‘Markup Languages and Reproducible Programming in Statisitcs’ (research master), lectures (2023-2024, 2024-2025), guest lecture (2021-2022, 2022-2023), grading (2022-2023, 2023-2024, 2024-2025)

2020-current
  • Applied Data Analysis and Visualization (advanced undergraduate), guest lecture (2020-2021, 2021-2022, 2022-2023, 2023-2024, 2024-2025), work groups and grading (2020-2021)

2017-2018
  • ‘Practicum cognitieve en neurobiologische psychologie’ (advanced undergraduate), supervising practicals (2017-2018)

2016-2017
  • ‘Experimenting and registering’ (advanced undergraduate), supervising practicals (2016-2017)

Qualitative research methodology

2020-2022
  • ‘Technieken voor analyse kwalitatieve en kwantitatieve gegevens (TAK)’ (advanced undergraduate), supervising practicals (2020-2021, 2021-2022)

2018-2019
  • ‘Advanced Research Methods and Statistics’ (advanced undergraduate), developing assignments, grading, teaching work groups, and supervising practicals (2018-2019)

2018-2019
  • ‘Doing a Qualitative Research Project’ (advanced undergraduate), developing assignments, lecturing, teaching work groups, and supervising practicals (2018-2019)

2018-2019
  • ‘Qualitative Inquiry in Everyday Life (MET24)’ (advanced undergraduate), teaching work groups and supervising practicals (2018-2019)

Methodology and statistics

2024-current
  • ‘Kennismaking met onderzoeksmethoden en statistiek’ (introductory undergraduate), teaching work groups (2024-2025)

2020-current
  • ‘Verdieping Onderzoeksmethoden en Statistiek’ (advanced undergraduate), teaching work groups, and grading (2020-2021, 2022-2023, 2023-2024, 2024-2025)

2021-2022
  • ‘Basis van Onderzoeksmethoden en Statistiek’ (pre-master), teaching work groups, grading, and test organization (2021-2022)

2021-2022
  • ‘Bachelorthesis Pedagogische Wetenschappen’ (advanced undergraduate), consultancy in methodology & statistics labs (2021-2022)

2020-2022
  • ‘Advanced Research Methods and Statistics’ (advanced undergraduate), teaching work groups, grading, and test organization (2020-2021, 2021-2022)

2017-2018
  • ‘Toepassing van onderzoeksmethoden en statistiek’ (elaborating undergraduate), practicals (2017-2018)

Conferences

2024
  • Poster, ‘Teaching Reproducibility to Research Master’s Students’, NLRN, Groningen, The Netherlands

2024
  • Tutorial, ‘Missing data exploration, imputation, and evaluation’, useR!, Salzburg, Austria

2024
  • Tutorial, ‘Open (your) Science Using the Statistical Package JASP’, EMLAR, Utrecht, The Netherlands

2024
  • Presentation, ‘Data visualization for incomplete datasets in R’, Annual Meeting VVSOR, Utrecht, The Netherlands

2023
  • Presentation, ‘Towards a standardized evaluation of imputation methodology: potential pitfalls in simulation studies and a proposed course of action’, European Congress of Methodology EAM, Ghent, Belgium

2023
  • Poster presentation, ‘Visualization of incomplete and imputed data with the R package ggmice’, Summer Conference IOPS, Tilburg, The Netherlands

2021
  • Late-breaking work in progress, ‘Visualizing Uncertainty Due to Missing Data’, IEEE VIS workshop ‘VisComm: Visualization for Communication’ VIS2021, online

2021
  • Community led session, ‘Pre-registration of Data Science Studies’, Open Science Festival OSF2021NL, online

2020
  • Presentation, ‘Missing the Point: Non-Convergence in Iterative Imputation Algorithms’, International Conference on Machine Learning (ICML) workshop ‘ARTEMISS: The Art of Learning with Missing Values’ ICML, online

2019
  • Pre-study poster presentation, ‘ShinyMICE: Developing a Missing Data Evaluation Suite (Master’s Thesis Methodology and Statistics)’, Society for the Improvement of Psychological Science (SIPS) conference SIPS2029, Rotterdam, The Netherlands

2018
  • Showcase, ‘Creativity and the Liberal Arts’, Global Academy of Liberal Arts (GALA) Annual Conference GALA, Montréal, Canada

2018
  • Invited talk, ‘Creating Creativity? Assessing adaptive expertise in Liberal Education students’, European Liberal Education Student Conference LESC, Utrecht, The Netherlands

2016
  • Poster presentation, ‘Assessing Adaptive Expertise in Higher Education Students’, Utrecht Platform for Creativity in Education (UPCE) conference UPCE, Utrecht, The Netherlands

2016
  • Workshop, ‘The interdisciplinary research process in practice’, National Interdisciplinary Education (NIE) Conference NIE, Amsterdam, The Netherlands

Footnotes

  1. Currently: permanent position as junior assistant professor (combined PhD candidate-lecturer role); after completion of PhD: permanent position as assistant professor↩︎