JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 475
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract - #304574
Title: The Impact of Covariance Misspecification in Multivariate Gaussian Mixtures on Estimation and Inference: An Application to Trajectory Modeling
Author(s): Brianna Heggeseth*+ and Nicholas Jewell
Companies: University of California at Berkeley and University of California at Berkeley
Address: Department of Statistics, Berkeley, CA, 94720, United States
Keywords: covariance ; model misspecification ; mixture models ; Kullback-Leibler divergence

Multivariate Gaussian mixtures are a class of models that provide a flexible parametric approach for the representation of heterogeneous multivariate outcomes. When the outcome is a trajectory vector of observations taken over time, there is often inherent dependence between measurements. However, one of the most used covariance assumption is conditional independence, which assumes that given the mixture component label, the outcomes for an observation unit are independent of each other. In this paper, we study, through asymptotic bias calculations and simulation, the impact of covariance misspecification in multivariate Gaussian mixtures. Although maximum likelihood estimators of parameters are not consistent under misspecification, they have little asymptotic bias when mixture components are well-separated even when outcomes are wrongly assumed to be conditionally independent. We also present a robust standard error estimator and show that it outperforms conventional estimators in simulations when the model is misspecified. Body mass index data from a national longitudinal study is used to demonstrate the effects of misspecification on potential inferences made in practice.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.