The Journal of Postsecondary Education and Disability · 2012 · 82 citations · 21 references
EducationHigher EducationSpecial EducationDisabilityDisability ManagementDisability PolicyDisability DataDisability StatisticsDropout PredictionGraduation AnalysisLogistic Regression ApproachesStudent SuccessDemographic Data ExtractionDisability In EducationDisability Status AnalysisExploratory Case StudyHierarchical Logistic RegressionPredictive Modeling Of GraduationSelection ModelStudent Success Prediction
This exploratory study determined which set of student characteristics and disability-related services explained graduation success among college students with disabilities. The archived records of 1,289 unidentified students with disabilities in three public universities were examined ex-post-facto to collect demographic data on the students, the disability-related services they qualified for while enrolled in the institution, and student graduation status. A hierarchical logistic regression framework was used to compare models predicting graduation among students with disabilities in college. A model selection procedure was then used to construct a parsimonious model of the data. The final model constructed included predictors related to gender, age, disability type, and several disability-related services. Given the limitations of this study, more research is needed to validate this model using a similar sample of students with disabilities in 2-year and 4-year institutions.
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