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Predictors of Categorical At‐Risk High School Dropouts
Author(s) -
Suh Suhyun,
Suh Jingyo,
Houston Irene
Publication year - 2007
Publication title -
journal of counseling and development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.805
H-Index - 78
eISSN - 1556-6676
pISSN - 0748-9633
DOI - 10.1002/j.1556-6678.2007.tb00463.x
Subject(s) - dropout (neural networks) , categorical variable , logistic regression , socioeconomic status , psychology , demography , longitudinal study , national longitudinal surveys , school dropout , statistics , mathematics education , mathematics , sociology , socioeconomics , computer science , population , machine learning
The authors attempted to identify key contributing factors to school dropout among 3 categories of at‐risk students: those with low grade point averages, those who had been suspended, and those from low socioeconomic backgrounds. Logistic regression analysis of the data, which were derived from the National Longitudinal Survey of Youth‐1997 (U.S. Bureau of Labor Statistics, 2002) indicated that student dropout rates were affected differently by students' membership in the 3 at‐risk categories.