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: 72
Type: Contributed
Date/Time: Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Computing
Abstract - #306726
Title: A Discussion on Quadrature for Latent Variable Models with Categorical Responses
Author(s): Xiangxiang Meng*+ and Xinming An
Companies: SAS Institute and SAS Institute
Address: 100 SAS Campus Dr, Cary, NC, 27513-8617, United States
Keywords: Gauss-Hermite quadrature ; adaptive quadrature ; generalized linear mixed model ; item response theory ; numerical integration

The estimation in latent variable models with categorical responses, such as generalized linear mixed models (GLMM) and item response models (IRT), often involves integration that cannot be solved analytically. Numerous approaches have been proposed to tackle this problem, among which numerical integration, for example Gauss-Hermite quadrature, has proven to generate more accurate estimations as compared with other methods. G-H quadrature with 20 points per dimension is widely considered to be able to produce quality estimations. However, several researches have reported unstable or biased estimations even with more than 20 quadrature points per dimension under some special conditions, for example when the variances of latent variables are large. The objective of this research is to investigate when and why standard G-H quadrature will be inadequate even with a large number of quadrature

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.