Comparing Methodologies for Developing an Early Warning System : Classification and Regression Tree Model versus Logistic Regression. REL 2015-077 / Sharon Koon and Yaacov Petscher.

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 i...

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Bibliographic Details
Online Access: Full Text (via ERIC)
Main Authors: Koon, Sharon, Petscher, Yaacov (Author)
Corporate Authors: National Center for Education Evaluation and Regional Assistance (U.S.), Regional Educational Laboratory Southeast, Florida Center for Reading Research
Format: eBook
Language:English
Published: [Place of publication not identified] : Distributed by ERIC Clearinghouse, 2015.
Subjects:

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245 1 0 |a Comparing Methodologies for Developing an Early Warning System :  |b Classification and Regression Tree Model versus Logistic Regression. REL 2015-077 /  |c Sharon Koon and Yaacov Petscher. 
264 1 |a [Place of publication not identified] :  |b Distributed by ERIC Clearinghouse,  |c 2015. 
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500 |a Abstractor: As Provided.  |5 ericd. 
500 |a Educational level discussed: Grade 1. 
500 |a Educational level discussed: Primary Education. 
500 |a Educational level discussed: Elementary Education. 
500 |a Educational level discussed: Early Childhood Education. 
500 |a Educational level discussed: Grade 2. 
516 |a Text (Reports, Research) 
520 |a 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 which students are identified as at-risk or not at-risk readers. Logistic regression and CART were compared using data on a sample of grades 1 and 2 Florida public school students who participated in both interim assessments and an end-of-the year summative assessment during the 2012/13 academic year. Grade-level analyses were conducted and comparisons between methods were based on traditional measures of diagnostic accuracy, including sensitivity (i.e., proportion of true positives), specificity (proportion of true negatives), positive and negative predictive power, and overall correct classification. Results indicate that CART is comparable to logistic regression, with the results of both methods yielding negative predictive power greater than the recommended standard of .90. Details of each method are provided to assist analysts interested in developing early warning systems using one of the methods. Two appendixes include: (1) Literature Review; and (2) Technical details on methods and additional results. 
524 |a Regional Educational Laboratory Southeast.  |2 ericd. 
650 0 7 |a Classification.  |2 ericd. 
650 0 7 |a Regression (Statistics)  |2 ericd. 
650 0 7 |a Models.  |2 ericd. 
650 0 7 |a At Risk Students.  |2 ericd. 
650 0 7 |a Reading Difficulties.  |2 ericd. 
650 0 7 |a Comparative Analysis.  |2 ericd. 
650 0 7 |a Grade 1.  |2 ericd. 
650 0 7 |a Grade 2.  |2 ericd. 
650 0 7 |a Elementary School Students.  |2 ericd. 
650 0 7 |a Public Schools.  |2 ericd. 
650 0 7 |a Accuracy.  |2 ericd. 
650 0 7 |a Identification.  |2 ericd. 
650 0 7 |a Statistical Analysis.  |2 ericd. 
650 0 7 |a Nonparametric Statistics.  |2 ericd. 
650 0 7 |a Achievement Tests.  |2 ericd. 
650 0 7 |a Reading Tests.  |2 ericd. 
650 0 7 |a Predictive Validity.  |2 ericd. 
700 1 |a Petscher, Yaacov,  |e author. 
710 2 |a National Center for Education Evaluation and Regional Assistance (U.S.) 
710 2 |a Regional Educational Laboratory Southeast. 
710 2 |a Florida Center for Reading Research. 
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