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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
Peer reviewed Peer reviewed
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Koon, Sharon; Petscher, Yaacov; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
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…
Descriptors: At Risk Students, Reading Difficulties, Identification, Reading Comprehension
Foorman, Barbara R.; Petscher, Yaacov; Schatschneider, Chris – Florida Center for Reading Research, 2015
The Florida Center for Reading Research (FCRR) Reading Assessment (FRA) consists of computer-adaptive reading comprehension and oral language screening tasks that provide measures to track growth over time, as well as a Probability of Literacy Success (PLS) linked to grade-level performance (i.e., the 50th percentile) on the reading comprehension…
Descriptors: Elementary School Students, Middle School Students, High School Students, Written Language