Understanding Disproportionate Suspensions of Minority Students and Students with Disabilities: A Multilevel Approach
Krezmien, Michael Patrick
Leone, Peter E
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This paper presents the findings from an investigation of suspension practices in Maryland. Logistic regression analysis, discriminant analysis, and hierarchical generalized linear modeling were employed to understand the individual characteristics and school characteristics associated with risk for suspension of secondary age students in Maryland public schools. The findings from the HGLM analyses revealed substantial variability in the suspension practices of schools, and indicated that school-level characteristics accounted for a majority of the explained variance in the suspensions of youth in Maryland. A number of school factors were significantly associated with suspensions of youth when Race and Disability were controlled as level-1 predictors. Race and Disability were significant and robust predictors of the suspensions even when school-level factors were controlled. Results from this investigation are reported and discussed, and limitations to interpretation of the findings are described.