Iris Eekhout

PhD, Statistician

I work as a statistician at the unit Healthy Living & Work, where I conduct innovative research in methodological, statistical and societal topics. I work on innovative measurement for early child development (D-score), efficient measurement solutions, such as adaptive testing, dynamic web-applications and visualisations of statistical information, analyzing reliability and rater agreement, multiple imputation, longitudinal and multilevel analyses.

The D-score translates the results of different developmental milestones into a single unit for age 0-4. The D-score for child development is comparable with the unit meter for height and kg for weight and depicts a development trajectory increasing with age similar to growth curves for height and weight.

In international collaborations, I work on making the D-score a global measure to compare early child development between populations. These advances expand the use of the D-score by including milestones from over 20 international tools that assess early child development. The expansion of the D-score allows the comparison of development between children, or groups of children, who were measured with different tools. The latest innovation was an adaptive test to measure D-score.

Nationally, I work on dynamic web applications that support professionals in the Dutch Youth Health care, to work with innovations such as the D-score. Together with professionals, I adapt these web applications to improve feasibility and usability in practice. The tools that I develop are aimed to support professions to cope with changes, such as more flexible clinic visits, and digitalization. Examples of tools are “Van Wiechen Continue” that supports professionals to select the developmental milestones that fit with the age and developmental level of the child.

Recent publications

  • Child Development with the D-score | Research Gateways | Gates Open Research
  • Eekhout, I., van Buuren, S., Visser, B., Bink, M. C. A. M., & Huisman, A. (2023). Longitudinal individual predictions from irregular repeated measurements data. Scientific Reports.
  • Mokkink, L. B., de Vet, H., Diemeer, S., & Eekhout, I. (2022). Sample size recommendations for studies on reliability and measurement error: an online application based on simulation studies. Health Services and Outcomes Research Methodology, 1–25.

Leiden - Sylviusweg

Sylviusweg 71
NL-2333 BE Leiden