Linear latent structure analysis and modelling of multiple categorical variables
Publication
, Journal Article
Akushevich, I; Kovtun, M; Manton, KG; Yashin, AI
Published in: Computational and Mathematical Methods in Medicine
January 1, 2009
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.
Duke Scholars
Published In
Computational and Mathematical Methods in Medicine
DOI
EISSN
1748-6718
ISSN
1748-670X
Publication Date
January 1, 2009
Volume
10
Issue
3
Start / End Page
203 / 218
Related Subject Headings
- Bioinformatics
- 4901 Applied mathematics
- 4003 Biomedical engineering
- 0903 Biomedical Engineering
- 0102 Applied Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Akushevich, I., Kovtun, M., Manton, K. G., & Yashin, A. I. (2009). Linear latent structure analysis and modelling of multiple categorical variables. Computational and Mathematical Methods in Medicine, 10(3), 203–218. https://doi.org/10.1080/17486700802259798
Akushevich, I., M. Kovtun, K. G. Manton, and A. I. Yashin. “Linear latent structure analysis and modelling of multiple categorical variables.” Computational and Mathematical Methods in Medicine 10, no. 3 (January 1, 2009): 203–18. https://doi.org/10.1080/17486700802259798.
Akushevich I, Kovtun M, Manton KG, Yashin AI. Linear latent structure analysis and modelling of multiple categorical variables. Computational and Mathematical Methods in Medicine. 2009 Jan 1;10(3):203–18.
Akushevich, I., et al. “Linear latent structure analysis and modelling of multiple categorical variables.” Computational and Mathematical Methods in Medicine, vol. 10, no. 3, Jan. 2009, pp. 203–18. Scopus, doi:10.1080/17486700802259798.
Akushevich I, Kovtun M, Manton KG, Yashin AI. Linear latent structure analysis and modelling of multiple categorical variables. Computational and Mathematical Methods in Medicine. 2009 Jan 1;10(3):203–218.
Published In
Computational and Mathematical Methods in Medicine
DOI
EISSN
1748-6718
ISSN
1748-670X
Publication Date
January 1, 2009
Volume
10
Issue
3
Start / End Page
203 / 218
Related Subject Headings
- Bioinformatics
- 4901 Applied mathematics
- 4003 Biomedical engineering
- 0903 Biomedical Engineering
- 0102 Applied Mathematics