|
Activity Number:
|
139
- Challenges and Advances in Statistical Inference for Problems with Nonregularity in the Era of Big Data
|
|
Type:
|
Invited
|
|
Date/Time:
|
Monday, July 31, 2017 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
WNAR
|
|
Abstract #321857
|
|
|
Title:
|
Model-Robust Inference for Continuous Threshold Regression Models
|
|
Author(s):
|
Chongzhi Di and Ying Huang and Peter Gilbert and Youyi Fong*
|
|
Companies:
|
Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center
|
|
Keywords:
|
profile likelihood ratio under model misspecification ;
regression kink ;
immune correlates studies
|
|
Abstract:
|
Threshold regression models allow the relationship between the outcome and a covariate of interest to change across a threshold value in the covariate. Continuous threshold regression models may provide a useful summary of the association between outcome and the covariate of interest because they offer a balance between flexibility and simplicity. Motivated by collaborative works in studying immune response biomarkers of transmission of infectious diseases, we study hypothesis testing and estimation of continuous threshold models with particular attention on inference under model misspecification. The methods are illustrated with real data examples from the HIV-1 immune correlates studies.
|
Authors who are presenting talks have a * after their name.
