|
Activity Number:
|
424
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Nonparametric Statistics
|
| Abstract - #305309 |
|
Title:
|
Semiparametric Sequential Optimal Designs for Binary Response Models
|
|
Author(s):
|
Joseph Warfield*+ and Anindya Roy
|
|
Companies:
|
Johns Hopkins University Applied Physics Laboratory and University of Maryland, Baltimore County
|
|
Address:
|
11100 Johns Hopkins Rd, Laurel, MD, 20723,
|
|
Keywords:
|
Isotonic Smoothing Spline ; Link Function ; Sequential Design
|
|
Abstract:
|
The work in this paper deals with sequential designs for binary regression models, where the link functions are from a location scale family. We assume the functional form of the link function to be known, which leads to the unknown parameters and quantiles of the curve being of primary interest. We provide an empirical study to investigate the robustness of several sequential designs for binary regression models under different stimulus-response curves for two applications: Phase I clinical trial and reliability sensitivity testing. We propose nonparametric estimation of the stimulus-response curve via isotonic smoothing spline estimator under monotonicity constraint and incorporate the estimator into the sequential allocation scheme. This makes the procedure more robust against incorrect specification of the curve and at the same time maintains the objective of efficient estimation.
|
