Title

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 Department

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

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