Stef van Buuren

Professorship chair

Statistical Analysis of Incomplete Data (Utrecht University).

Research area

Imagine a world where realizing every child's growth and development potential is not just a hope but a reality. At TNO, my research is at the forefront of this vision, crafting cutting-edge quantitative methods to unlock the mysteries of child growth and development.

But what about the gaps and inconsistencies that often plague our data? Fear not, for I've devised robust strategies like Multiple Imputation by Chained Equations (MICE) to seamlessly fill in those gaps, ensuring no child's potential is overlooked due to missing information. And when data from different sources don't seem to align, my work in tackling data incomparability ensures that we can still draw meaningful conclusions, turning even the most varied datasets into a cohesive story of development and growth.

My secret weapon? Breaking down complex statistical analyses into smaller, digestible steps, making the intricate world of stats accessible to everyone. This isn't just about making my job easier—it's about empowering colleagues and clients with the clarity they need to make informed decisions. We're not just analyzing data; we're paving the way for a future where solid, actionable insights support every child's developmental journey.

Join us in this mission, and let's unlock the full potential of our next generation together.

Top publications

• van Buuren, S., & Groothuis-Oudshoorn, K. (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1–67. https://doi.org/10.18637/jss.v045.i03
• van Buuren, S. (2018). Flexible Imputation of Missing Data. Second Edition. Boca Raton, FL: Chapman & Hall/CRC Press. https://stefvanbuuren.name/fimd/
• Weber, A. M., Rubio-Codina, M., Walker, S. P., van Buuren, S., Eekhout, I., Grantham-McGregor, S. M., et al. (2019). The D-score: A metric for interpreting the early development of infants and toddlers across global settings. BMJ Global Health, 4(6). doi: 10.1136/bmjgh-2019-001724.