|
Activity Number:
|
582
- Nonparametric Methods for Statistical Inference
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Nonparametric Statistics
|
|
Abstract #304404
|
Presentation
|
|
Title:
|
Maximum Approximate Bernstein Likelihood Estimation in Proportional Hazard Model for Interval-Censored Data
|
|
Author(s):
|
Zhong Guan*
|
|
Companies:
|
Indiana University South Bend
|
|
Keywords:
|
Proportional Hazard Regression Model;
Interval Censoring;
Survival Curve;
Density Estimation;
Maximum Likelihood Estimation
|
|
Abstract:
|
Maximum approximate Bernstein likelihood estimates of density function and regression coefficients in the proportional hazard regression models based on interval-censored data are proposed and studied. A smooth estimate of the survival function with a bootstrap confidence interval is then obtained. Simulation study is conducted to show the finite sample performance of the proposed method. The proposed method is illustrated by real data applications.
|
Authors who are presenting talks have a * after their name.
