We are Tilburg University

We are Tilburg University

Bio

I’m passionate about health and statistics, and aim to combine these two to make my contribution to health care. My research focuses on improving and developing efficient statistical decision procedures for clinical trials, such that fewer participants are needed to test the effects of new treatments. My work is supported by an NWO Research Talent grant “Making the most of clinical trials: Increasing efficiency using novel Bayesian methods for information sharing within and between trials”. Currently, I am developing a Bayesian framework to make decisions based on multiple binary outcomes, while monitoring incoming data (i.e. in an adaptive trial).

Recente publicaties

  1. Decision-making with multiple correlated binary outcomes in clinical …

    Kavelaars, X., Mulder, J., & Kaptein, M. (2020). Decision-making with multiple correlated binary outcomes in clinical trials. Statistical Methods in Medical Research, 29(11), 3265-3277.
  2. Going multivariate in clinical trial studies - A Bayesian framework f…

    Kavelaars, X. (2020). Going multivariate in clinical trial studies: A Bayesian framework for multiple binary outcomes. In R. van de Schoot, & M. Miočević (Eds.), Small sample size solutions: A guide for applied researchers and practitioners Routledge.
  3. Multiple imputation in data that grow over time - A comparison of thr…

    Kavelaars, X. M., Buuren, S. V., & Ginkel, J. R. V. (2019). Multiple imputation in data that grow over time: A comparison of three strategies. arXiv.org.
  4. Potential impact of maternal vaccination on life-threatening respirat…

    Scheltema, N. M., Kavelaars, X. M., Thorburn, K., Hennus, M. P., van Woensel, J. B., van der Ent, C. K., Borghans, J. A. M., Bont, L. J., & Drylewicz, J. (2018). Potential impact of maternal vaccination on life-threatening respiratory syncytial virus infection during infancy. Vaccine, 36(31), 4693-4700.

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