Linear latent structure analysis and modelling of multiple categorical variables

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.

Keywords:

• latent structure analysis
• grade of membership
• population heterogeneity
• mortality
• NLTCS data
• disability
• simulation studies

Acknowledgements

This research was supported by Grant Nos. P01 AG17937-05, 5P01-AG08761-16, 5UO1-AG007198-18 and R01 AG28259-01 from National Institute on Ageing.