报告题目: Moving beyond Population Variable Importance: Concept, Theory and Applications of Individual Variable Importance

报告人：戴国榕，复旦大学管理学院

时间：2024年3月26日（周二）下午4:00-5:30          地点：理科楼A404

摘要: In a nonparametric regression setting, we propose a novel concept of ''individual variable importance'', which refers  to the relevance of some covariates with respect to an outcome variable among individuals with certain features. This concept holds practical importance for both risk assessment and association identification. For example, it can represent (i) the   usefulness of expensive biomarkers in disease prediction for individuals at certain baseline risk, or (ii) age-specific   associations between physiological indicators. We quantify the individual variable importance by a ratio parameter between  two conditional mean squared errors. To infer this parameter we develop fully nonparametric estimators and establish their   asymptotic properties. Our inferential approaches perform well in simulation studies. We further demonstrate our approaches through application to a real data set, showing a scientifically interesting result: the association between body shape and  systolic blood pressure decays with increasing age. While our finding aligns with the existing medical literature based on   standard parametric regression techniques, our analysis methods are more reliable because their validity is not affected by model misspecification. More importantly, the fully nonparametric nature equips the individual variable importance framework  with broader applicability in contexts that go beyond traditional parametric modeling. It can capture complex relationships  between variables that are likely to be missed by standard parametric interaction analyses. 

邀请人：杨瑛