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Latent Class Analysis for Multiple Discrete Latent Variables: A Study on the Association Between Violent Behavior
Saebom Jeon1, Jungwun Lee2, James C Anthony3
1Department of Marketing Information Consulting, Mokwon University.
Summary
This study introduces joint latent class analysis (JLCA) to identify patterns in adolescent behaviors. JLCA reveals common joint classes for violence and substance use among young males.
Area of Science:
- Social Sciences
- Criminology
- Public Health
Background:
- Adolescent behavioral patterns, including violence and substance use, are complex and often co-occur.
- Understanding these joint patterns is crucial for effective prevention and intervention strategies.
- Existing statistical methods may not fully capture the intricate relationships between multiple behavioral variables.
Purpose of the Study:
- To introduce and validate a novel statistical approach, joint latent class analysis (JLCA), for analyzing multiple discrete latent variables.
- To systematically identify subsets of joint patterns among adolescent violent behavior and drug-using behaviors.
- To investigate the co-occurrence of specific violent and substance use behaviors in adolescent males.
Main Methods:
- Development of joint latent class analysis (JLCA) principles for identifying joint patterns of multiple discrete latent variables.
- Application of a hybrid Expectation-Maximization (EM) and Newton-Raphson algorithm for parameter inference.
- Utilizing data from the Youth Risk Behavior Surveillance System (YRBSS) 2015, including 4,957 male high-school students.
Main Results:
- The JLCA approach successfully identified distinct joint patterns across four latent variables: violent behavior, alcohol consumption, tobacco cigarette smoking, and other drug use.
- Four common patterns of violent behavior and three representative patterns for each of alcohol, tobacco, and other drug use were uncovered.
- Three common joint classes were identified, illustrating the most probable simultaneous patterns of violent and drug-using behaviors among adolescent males.
Conclusions:
- Joint latent class analysis (JLCA) is an effective method for uncovering complex behavioral patterns in adolescents.
- The findings highlight specific co-occurring patterns of violence and substance use, providing valuable insights for targeted interventions.
- JLCA offers a robust framework for future research on the interplay of multiple risk behaviors in adolescent populations.
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