Abstract Details
Activity Number:
|
653
|
Type:
|
Contributed
|
Date/Time:
|
Thursday, August 13, 2015 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Biometrics Section
|
Abstract #316888
|
|
Title:
|
A Finite Mixture Logistic-Gaussian Model for Zero-Inflated Clustered Binary Data
|
Author(s):
|
John Kwagyan* and Victor Apprey and Nana Osafo
|
Companies:
|
Howard University and Howard University and Howard University
|
Keywords:
|
Clustered binary data ;
Logistic-Gaussian model ;
random effect models ;
zero-inflated models ;
Gaussian quadratures
|
Abstract:
|
We establish a finite mixture model for clustered binary data in which all members of clusters in one latent class have a zero response with probability one; and clusters in the other latent class yield correlated outcomes. Response probabilities in terms of fixed effect and random effects models are formulated, and estimation procedures based on Gaussian Quadrature and a combined EM with Gaussian Quadrature are developed. Application to esophageal cancer data in Chinese families is presented.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2015 program
|
For program information, contact the JSM Registration Department or phone (888) 231-3473.
For Professional Development information, contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
2015 JSM Online Program Home
ASA Meetings Department
732 North Washington Street, Alexandria, VA 22314
(703) 684-1221 • meetings@amstat.org
Copyright © American Statistical Association.