The purpose of this study was to create and test two series of predictive models aimed at projecting high school graduation status. Secondary data were obtained in partnership with an urban school district. All of the predictor variables included in the models tested in this study were academic and nonacademic variables that were found to be significant predictors of high school graduation in previous empirical work. In the first series of models tested, individual academic and nonacademic variables were tested together along with school-level variables. Eighth and ninth grade variables were tested separately to avoid multicollinearity issues. The second series of models tested included similar individual-level academic and nonacademic variables, along with community-level predictors to analyze their ability to predict high school graduation status. Logistic regression and multilevel logistic regression analyses were conducted to analyze the data. The model including community-level predictors yielded a pseudo R-squared value of .40, approximating that 40% of the variance was explained by the predictors in the model. Most of the individual predictors included in the models yielded findings similar to those found in previous literature on high school graduation status projection; however, this was not true for all of the predictor variables included. These differences highlight the tension that can exist between generalizability and local specificity. Significant findings from studies utilizing large nationally-representative longitudinal datasets and other large data sources do not always generalize to settings with samples that differ demographically. This study represents a first step in a line of research aimed at developing a better understanding of high school graduation status, particularly in challenging school contexts.
| Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-5802 |
| Date | 01 January 2017 |
| Creators | Marshall, David T. |
| Publisher | VCU Scholars Compass |
| Source Sets | Virginia Commonwealth University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | © David T. Marshall 2017 |
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