Work

Multilevel Latent Class Analysis: An Application of Adolescent Smoking Typologies With Individual and Contextual Predictors

Year: 2010

Type: article

Abstract: Latent Class Analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical and/or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this paper, a new methodology, multilevel latent class analysis (MLCA), is described and an applied example is presented. Latent classes of cigarette smoking among 10,772 European American females in 9th grade who live in one of 206 rural communities across the U.S. are considered. A parametric and non-parametric approach for estimating a MLCA are presented and both individual and contextual predictors of the smoking typologies are assessed. Both latent class and indicator-specific random effects models are explored. The best model was comprised of three Level 1 latent smoking classes (heavy smokers, moderate smokers, non-smokers), two random effects to account for variation in the probability of Level 1 latent class membership across communities, and a random factor for the indicator-specific Level 2 variances. Several covariates at the individual and contextual level were useful in predicting latent classes of cigarette smoking as well as the individual indicators of the latent class model. This paper will assist researchers in estimating similar models with their own data.

Source: Structural Equation Modeling A Multidisciplinary Journal

DOI: 10.1080/10705511003659342

Authors: Kimberly L. Henry, Bengt Muthén

Institutions: Colorado State University, University of California, Los Angeles, University of California System

Language: English

Topic: Psychometric Methodologies and Testing

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institute on Alcohol Abuse and Alcoholism, National Institute of Mental Health, National Institute on Drug Abuse