The assessment of screening accuracy and setting of cut points for a universal screener have traditionally been evaluated using logistic regression analysis. This analytic technique has been frequently used to evaluate the trade-offs in correct classification with misidentification of individuals who are at risk of performing poorly on a later…

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…

This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…

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.…