Latent Class-Profile Analysis: An Application to Stage-Sequential Process of Under-Age Drinking Behaviors

• Activity Number: 293
• Type: Topic Contributed
• Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Health Policy Statistics Section
• Author(s): Hwan Chung*+
• Companies: Ewha Womans University
• Keywords: Finite mixture ; Latent class analysis ; Longitudinal data ; Maximum likelihood ; Marcov chain Monte Carlo ; Stage-sequential process

Abstract

Research on the sequential development of alcohol use can be challenging in part because the stage of drinking behavior at a certain time point may not be directly observable. In this context, a latent class analysis (LCA) can provide a set of principles for systematic identification of homogeneous subgroups. We propose an LCA approach, referred to as a latent class-profile analysis (LCPA), for investigating the stage-sequential patterns of drinking behavior. The LCPA characterizes different drinking patterns in terms of a small number of classes based on responses to items at each measurement occasion; and then it examines class sequencing over the entire time points so as to identify two or more homogeneous subgroups. Inferences about the model parameters are obtained by a combination of ML and Bayesian techniques, and their properties are investigated through a simulation study.