UW Biiostatistics & Medical Informatics UW Biostatistics & Medical Informatics UW Madison UW Biostatistics & Medical Informatics Site Map
UW School of Medicine and Public Health UW Madison


 

 


Other Seminar Series

Seminars

General Departmental Seminar Series


Selecting the Number of Classes under Latent Class Regression Models: A Factor Analysis Analogous Approach

Guan-Hua Huang, Departments of Preventive Medicine
and Biostatistics and Medical Informatics,
University of Wisconsin

Friday, Mar 9, 2001, 12:00-1:00 p.m.

3285 Medical Sciences Center - 1300 University Ave.

ABSTRACT

Recently, the latent class regression (LCR) model has received much attention in the field of medical research. The basic LCR model summarizes shared features of measured multiple indicators as an underlying categorical variable and incorporates the covariate information in modeling both latent class membership and the multiple indicators themselves. To reduce complexity and enhance interpretability, one usually fixes the number of classes in a given LCR. Often, goodness of fit methods comparing various estimated models are used as a criterion to select the number of classes. In this talk, I propose a new method which is based on an analogous method used in factor analysis and does not require repeated fitting. Two ideas with application to many settings other than ours are synthesized in deriving the method: a connection between latent class models and factor analysis, and techniques of covariate marginalization and elimination. A Monte Carlo simulation study is presented to evaluate the behavior of the selection procedure.


Back to General Departmental Seminar Series

 

Internal Use | Site Map | Search |
Overview | People | Training | Research | Seminars | Employment | Links |
Biostatistics Program | Clinical Trials Program | Medical Informatics Program | Biomedical Computing |

Copyright © 2006 The Board of Regents of the
University of Wisconsin System

 

UW Madison UW School of Medicine and Public Health