Computational and Mathematical Methods in Medicine

Computational and Mathematical Methods in Medicine / 2009 / Article

Original Article | Open Access

Volume 10 |Article ID 279684 | https://doi.org/10.1080/17486700802259798

I. Akushevich, M. Kovtun, K. G. Manton, A. I. Yashin, "Linear Latent Structure Analysis and Modelling of Multiple Categorical Variables", Computational and Mathematical Methods in Medicine, vol. 10, Article ID 279684, 16 pages, 2009. https://doi.org/10.1080/17486700802259798

Linear Latent Structure Analysis and Modelling of Multiple Categorical Variables

Received18 Jul 2007
Accepted29 May 2008

Abstract

Linear latent structure analysis is a new approach for investigation of population heterogeneity using high-dimensional categorical data. In this approach, the population is represented by a distribution of latent vectors, which play the role of heterogeneity variables, and individual characteristics are represented by the expectation of this vector conditional on individual response patterns. Results of the computer experiments demonstrating a good quality of reconstruction of model parameters are described. The heterogeneity distribution estimated from 1999 National Long Term Care Survey (NLTCS) is discussed. A predictive power of the heterogeneity scores on mortality is analysed using vital statistics data linked to NLTCS.

Copyright © 2009 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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