A latent transition model with logistic regression
- Authors
- Chung, Hwan; Walls, Theodore A.; Park, Yousung
- Issue Date
- 9월-2007
- Publisher
- SPRINGER
- Keywords
- latent transition; logistic regression; MCMC; academic achievement
- Citation
- PSYCHOMETRIKA, v.72, no.3, pp.413 - 435
- Indexed
- SCIE
SCOPUS
- Journal Title
- PSYCHOMETRIKA
- Volume
- 72
- Number
- 3
- Start Page
- 413
- End Page
- 435
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/125726
- DOI
- 10.1007/s11336-005-1382-y
- ISSN
- 0033-3123
- Abstract
- Latent transition models increasingly include covariates that predict prevalence of latent classes at a given time or transition rates among classes over time. In many situations, the covariate of interest may be latent. This paper describes an approach for handling both manifest and latent covariates in a latent transition model. A Bayesian approach via Markov chain Monte Carlo (MCMC) is employed in order to achieve more robust estimates. A case example illustrating the model is provided using data on academic beliefs and achievement in a low-income sample of adolescents in the United States.
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- Appears in
Collections - College of Political Science & Economics > Department of Statistics > 1. Journal Articles
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