Absenteeism among In-School Adolescents in South-West, Nigeria using Probit Regression Model
DOI:
https://doi.org/10.30442/Keywords:
Absenteeism, Determinants, In-school adolescents, Probit regression. Secondary school, SocialAbstract
Background: Adolescents face a lot of social, economic challenges and psychological well-being resulting to absenteeism, leading to poor performance in school. Many studies have identified determinants of absenteeism through logistic regression models. However, there are other models that are suitable to identify factors associated with a binary response variable like absenteeism.
Objective:To identify factors associated with absenteeism among in-school adolescents in Sagamu using probit model.
Methods: Secondary data from a descriptive cross-sectional study carried out among a representative sample of adolescents attending public secondary schools in Sagamu Township were used. Logistic and Probit regression models were used to identify the factors associated with absenteeism. The residual deviance (RD), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) were criteria for model comparison.
Results: The RD (778, 778), AIC (806, 806) and BIC (876, 876) for both models were the same. There was no difference in the performance of the two models.
Age (17-19yrs; β=0.413), Marital status (β=1.840), Consume alcohol (β=1.015), Poor comprehension (β=0.305), and loneliness (β=0.231) had positive significant association with absenteeism (p< 0.05). Smoking (β= -0.548, p=0.036) had negative significant association with absenteeism, while Sex, Mother’s education and occupation, and living arrangement were not significantly associated with absenteeism.
Conclusion: The logistic regression and probit models performed the same way. Age, marital status, alcohol consumption, poor comprehension, loneliness and smoking were determinants of absenteeism. Parents and school administrators should pay attention to the psychosocial factors identified when designing intervention to significantly reduce absenteeism.
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