This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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293
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Health Policy Statistics Section
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Abstract - #307154 |
Title:
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Latent Class-Profile Analysis: An Application to Stage-Sequential Process of Under-Age Drinking Behaviors
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Author(s):
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Hwan Chung*+
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Companies:
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Ewha Womans University
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Address:
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Department of Statistics, Seoul, International, 120-750, Korea
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Keywords:
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Finite mixture ;
Latent class analysis ;
Longitudinal data ;
Maximum likelihood ;
Marcov chain Monte Carlo ;
Stage-sequential process
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Abstract:
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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.
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Authors who are presenting talks have a * after their name.
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