JSM 2003 Online Program

Abstract #300771

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Activity Number:	315
Type:	Invited
Date/Time:	Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor:	IMS
Abstract - #300771
Title:	Nonlinear Latent Variable Analysis for Multivariate Non-normal Data
Author(s):	Yasuo Amemiya*+
Companies:	IBM T. J. Watson Research Center
Address:	1101 Kitchawan Rd., Route 134, Yorktown Heights, NY, 10598,
Keywords:	structural equation modeling ; measurement error models ; discrete response
Abstract:	In structural equation analysis of multivariate data, observed variables are assumed to be related to underlying factors, and relationships among the unobservable factors are of interest. This paper addresses a situation where the observations can be discrete or non-normal, and where the relationships of interest are expressed in a nonlinear model. The overall model is doubly nonlinear in the sense that both the measurement model and the structural model can be nonlinear. Estimation and inference for parameters are considered.

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