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Multilevel Latent Class Profile Analysis: An Application to Stage-Sequential Patterns of Alcohol Use in a Sample of
Yunah Lee1, Youngsun Kim1, Scott T Leatherdale2
1Department of Statistics, 34973Korea University, Seoul, South Korea.
Abstract:
Recently, latent class analysis (LCA) and its variants have been proposed to identify subgroups of individuals who follow similar sequential patterns of latent class membership for longitudinal study. A primary assumption underlying the family of LCA is that individual observations are independent. In many applications, however, particularly in research on adolescent substance use, individuals are often dependent because of multilevel data structure, where the unit of observation (e.g., students) is nested in higher level units (e.g., schools). In this study, we propose multilevel latent class profile analysis (MLCPA), which will allow us to analyze the longitudinal data with a multilevel structure under the framework of LCA. We apply an MLCPA using data from the COMPASS study, a 9-year study funded by the Canadian Institutes of Health Research and Health Canada, in order to identify representative sequential drinking patterns of Canadian youth and investigate whether these sequential patterns vary across schools. The MLCPA identified three common student-level drinking behaviors: non-drinker, ever lifetime, and binge drinker. The sequence of drinking behaviors can be classified into one of three longitudinal sequential patterns: non-drinking stayer, light drinking advancer, and heavy drinking advancer. In addition, MLCPA uncovered two latent clusters (low-use school and high-use school) out of 64 schools in Ontario and Alberta based on the prevalences of sequential drinking patterns.
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