Research

My research focuses on missing data methodology, with a particular interest in imputation algorithms. Reach out to me if you have questions about imputation with the R package {mice}, or if you want to collaborate on a project. I am also available for statistical consultation and workshops on missing data methodology .

For an overview of my published work, see my ORCID page. Other places to find my research output are my Utrecht University page, OSF, and Google Scholar. I aim to work open source and make my research repositories available on GitHub.

Development

Research output

2021-current | ggmice: Visualizations for mice with ggplot2 | R package with vignette on CRAN

2019-current | shinymice: Interactive evaluation for mice with shiny | R shiny web app with demo version and (upcoming) R package

Selected contributions

2024 | Toward a standardized evaluation of imputation methodology | Review article published in Biometrical Journal

2023 | Quality control, data cleaning, imputation | Book chapter in ‘Clinical Applications of Artificial Intelligence in Real-World Data’, available from ArXiv

2020 | Missing the point: non-convergence in iterative imputation algorithms | Conference paper presented at ICML, available from ArXiv