JSM 2004 - Toronto

Abstract #301276

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Activity Number: 102
Type: Topic Contributed
Date/Time: Monday, August 9, 2004 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #301276
Title: Latent Variable Modeling with Continuous and Classification Latent Variables
Author(s): Yasuo Amemiya*+ and Melanie M. Wall
Companies: IBM T.J. Watson Research Center and University of Minnesota
Address: Rm. 33-222 1101 Kitchawan Rd., Yorktown Heights, NY, 10598,
Keywords: latent class model ; structural equation analysis ; categorical response ; latent health condition ; psychological construct
Abstract:

There are two types of latent variable modeling often used in health sciences research; structural equation modeling with continuous factors, and latent class analysis with unordered-categorical latent segments. This paper develops a statistical methodology for a more general model with both continuous and categorical latent variables. Observed measurement types are allowed to include continuous and ordered categorical responses. Model-fitting methods and associated statistical inference procedures are discussed. This methodology can be useful in health science applications, where a health condition outcome variable is a latent classification, and some of possible predictor variables are psychological/behavioral constructs. An example relating a underlying eating disorder condition to a physical appearance satisfaction construct is presented.

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