Using national survey data and discrete-time logit modeling, this research seeks to understand whether student aid mediates the relationship between parental income and student dropout behavior. Our analysis confirms that there is a gap in dropout rates for low-income students compared with their upper income peers, and suggests that some types of aid are associated with lower risks of dropout. Thus, we examine the interaction between financial aid type and parental income to explore whether, and if so how, different types of aid may reduce the dropout gap by income level group. We find that the receipt of a Pell grant is related to narrowing the dropout gap between students from low- and middle-income groups, although overall the interaction between Pell grant and income is not significant. Loans and work-study aid both have similar effects on student dropout across all income groups. Methodologically, our results demonstrate the need to model dropout behavior temporally and to avoid main-effect bias by incorporating interaction effects.
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For more on these, see related sections in Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence by Singer and Willett (2003).
Although we have evidence of how the receipt of a Pell grant changes the predicted probabilities of dropout for middle income students, the interaction model (results displayed in Table 4) was not a significant improvement (P = .14) compared to the model without these interaction terms (results displayed in Table 3).
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This research was funded by the American Educational Research Association and the Association for Institutional Research. Their financial support is gratefully acknowledged. The findings and interpretations are, however, the authors’ and do not represent the policies or positions of the funding agencies.
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Chen, R., DesJardins, S.L. Exploring the Effects of Financial Aid on the Gap in Student Dropout Risks by Income Level. Res High Educ 49, 1–18 (2008). https://doi.org/10.1007/s11162-007-9060-9
- Financial aid
- Income differences
- Event history analysis
- Main-effect bias