JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 28
Type: Contributed
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract #316219 View Presentation
Title: Nonparametric Identifiability of Finite Mixture Models with Covariates
Author(s): Zheyu Wang* and Xiao-Hua Zhou
Companies: The Johns Hopkins University and University of Washington
Keywords: finite mixture models ; local identifiability ; global identifiability ; covariates ; diagnostic test ; gold standard
Abstract:

Finite mixture models provide a flexible framework to study unobserved entities and have arisen in many statistical applications. The flexibility of these models in adapting various complicated structures makes it crucial to establish model identifiability when applying them in practice to ensure study validity and interpretation. However, researches to establish the identifiability of finite mixture model are limited, especially when covariates are involved. In addition, most efforts have focused on finding conditions for local identifiability while global identifiability was rarely discussed. In this talk, we will discuss the different role of local and global identifiability, as well as the approaches for establishing local and global identifiability. The finite mixture model we considered here is constructed for estimating diagnostic error rate without a gold standard, which allows for continuous, discrete or mix-typed manifest variables, ordinal or nominal latent groups, and flexible inclusion of covariates. We also provide intuitive explanation of the conditions and discuss the effect of including covariates in the model.


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