A multivariate latent class profile analysis for longitudinal data with a latent group variable
- Authors
- Lee, Jung Wun; Chung, Hwan
- Issue Date
- 1월-2020
- Publisher
- KOREAN STATISTICAL SOC
- Keywords
- categorical latent variable; latent class analysis; latent stage-sequential process; longitudinal data; recursive EM algorithm
- Citation
- COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, v.27, no.1, pp.15 - 35
- Indexed
- SCOPUS
KCI
- Journal Title
- COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS
- Volume
- 27
- Number
- 1
- Start Page
- 15
- End Page
- 35
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/58566
- DOI
- 10.29220/CSAM.2020.27.1.015
- ISSN
- 2287-7843
- Abstract
- In research on behavioral studies, significant attention has been paid to the stage-sequential process for multiple latent class variables. We now explore the stage-sequential process of multiple latent class variables using the multivariate latent class profile analysis (MLCPA). A latent profile variable, representing the stage-sequential process in MLCPA, is formed by a set of repeatedly measured categorical response variables. This paper proposes the extended MLCPA in order to explain an association between the latent profile variable and the latent group variable as a form of a two-dimensional contingency table. We applied the extended MLCPA to the National Longitudinal Survey on Youth 1997 (NLSY97) data to investigate the association between of developmental progression of depression and substance use behaviors among adolescents who experienced Authoritarian parental styles in their youth.
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Collections - College of Political Science & Economics > Department of Statistics > 1. Journal Articles
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