ACMS Statistics Seminar: Haoda Fu

-

Location: 154 Hurley Hall

Haoda Fu
Eli Lilly

3:30 PM
154 Hurley Hall

Individualized Treatment Recommendation (ITR) for Survival Outcomes

ITR is a method to recommend treatment based on individual patient characteristics to maximize clinical benefit. During the past a few years, we have developed and published methods on this topic with various applications including comprehensive search algorithms, tree methods, benefit risk algorithm, multiple treatment & multiple ordinal treatment algorithms. In this talk, we propose a new ITR method to handle survival outcomes for multiple treatments. This new model enjoy the following practical and theoretical features.

- Instead of fitting the data, our method directly search the optimal treatment police which improve the efficiency.

- To adjust censoring, we propose a doubly robust estimator. Our method only requires either censoring model or survival model is correct, but not both. When both are correct, our method enjoys better efficiency.

- Our method handles multiple treatments with intuitive geometry explanations. - Our method is Fisher’s consistent even under either censoring model or survival model misspecification (but not both).

This is joint work with Karen Kazor.

 

Full List of Statistics Seminar Speakers


 


 


 

Screen Shot 2018 04 27 At 11

s