Profiling young adults and adolescents based on risk behaviors using latent class analysis
Date of Publication
2018
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Statistics Major in Actuarial Science
Subject Categories
Physical Sciences and Mathematics
College
College of Science
Department/Unit
Mathematics and Statistics
Abstract/Summary
Numerous literatures have stressed that detection of risk behaviors can assist a person towards reducing injury. Latent Class Analysis (LCA) was used in determining the optimal number of latent classes for six risk indicators variables: alcohol consumption in a day, cigarette smoking in a day, marijuana use in the past 30 days, number of sexual partners for the past 3 months, depression, and suicidal ideation. The analysis has resulted to four distinct latent classes: High Risk, Low Risk, Poor Mental Health, and Legal Substance User. The respondents were profiled using the Multiple-Group LCA, and the output has provided the prevalence of each socio-demographic trait (e.g. age, sex, family structure, social support, occupational status and socio-economic status) among the four latent classes formed.
Abstract Format
html
Language
English
Format
Electronic
Accession Number
CDTU017667
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Recommended Citation
Sison, C. S., & Soriano, K. A. (2018). Profiling young adults and adolescents based on risk behaviors using latent class analysis. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/18580
