Linear latent structure analysis and modelling of multiple categorical variables


Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Akushevich, I; Kovtun, M; Manton, KG; Yashin, AI

Published Date

  • September 21, 2009

Published In

Volume / Issue

  • 10 / 3

Start / End Page

  • 203 - 218

Electronic International Standard Serial Number (EISSN)

  • 1748-6718

International Standard Serial Number (ISSN)

  • 1748-670X

Digital Object Identifier (DOI)

  • 10.1080/17486700802259798

Citation Source

  • Scopus