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Koon, Sharon; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2015
The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…
Descriptors: Classification, Regression (Statistics), Models, At Risk Students
Johnson, Evelyn S.; Jenkins, Joseph R.; Petscher, Yaacov – Assessment for Effective Intervention, 2010
In a response-to-intervention framework, schools typically employ a direct route approach to screening, in which students identified as at risk by a screening process are directly placed into intervention. Direct route approaches require screening decisions to be highly accurate, but few studies examining the predictive validity of reading…
Descriptors: Screening Tests, Reading Tests, At Risk Students, Predictive Validity
Rubin, Rosalyn A.; And Others – 1976
Relationships between performance on two preschool administrations of the Metropolitan Readiness Tests (MRT) and Stanford Achievement Test (SAT) scores at age nine were examined for a sample of 732 children. Significant correlations, ranging from .50 to .71, were obtained between readiness scores and SAT scores on reading, spelling and arithmetic.…
Descriptors: Academic Achievement, Achievement Tests, Classification, Correlation