报告题目：Predictive Inference Using First-hitting-time Threshold Regression

报告时间：2024.06.27   14:00-15:00

报  告 人 ：丁美龄  教授  马里兰大学

报告地点：理学院东北楼二楼报告厅（209）

Abstract：Disease progression in a patient can be described mathematically as a process. The patient experiences a failure event when his/her disease progression first reaches a critical threshold level. This happening defines the failure event itself and the first hitting time (FHT) is the event time. First hitting time threshold regression (TR) models incorporate regression functions for parameters of the underlying process. These FHT TR models do not require the proportional hazards assumption and represent a realistic alternative to the Cox model. The FHT TR models can be used to analyze longitudinal time-to-event data. Some applications will be presented to demonstrate the usefulness of the model.