SURF

Dae Woong Ham

Synergy Analysis in Radiobiology using Incremental Effect Additivity

The current theory we are interested that is applicable in radiobiology uses a mathematically lacking model for specifically modelling dose and effect relationship. This lacking model is especially inappropriate for settings where the dose effect relations are highly curvilinear, which will seriously hinder many researchers from developing synergy theory, a concept of interest to many radiobiologists. We propose a better and more appropriate model to do synergy theory and modelling.
My SURF research, which will build from the research I have already been doing with my mentor, will continue to explore deeper into the statistical validity and robustness of our proposal through various techniques. To get a little bit more specific, some of the things that will be validated is appropriateness of fit and parsimony of our variables through methods such as cross validation and building alternative models.

Message to Sponsor

First of all thank you very much for this fellowship I really appreciate it. With this fellowship I was able to travel to the appropriate place to conduct my research, which meant using a stronger computer to do all my computationally expensive coding. This SURF experience has given me an opportunity to really strive for what I want, and only what I want, to the most professional level. I am planning to actually submit my SURF work to a very prestigious statistical journal called Journal of American Statistical Association. This experience have overall been a huge joy and help for not only my summer but also my long term graduate studies career.
  • Major: Applied Mathematics and Statistics
  • Sponsor: Anselm M&PS
  • Mentor: Rainer K. Sachs