JSM 2011 Online Program

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Abstract Details

Activity Number: 176
Type: Contributed
Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
Sponsor: Social Statistics Section
Abstract - #302541
Title: Modeling Score-Based Student Achievement Data with Many Ceiling Values
Author(s): Yan Yang*+
Companies: Arizona State University
Address: School of Math and Stats, Tempe, AZ, 85287-1804,
Keywords: Censoring ; EM algorithm ; mixed effects ; Tobit model ; value-added modeling
Abstract:

The competitive federal Race to the Top grant program relies on standards-based state assessments to measure student achievement and school performance. In a standards-based test, high-performing students may achieve the maximum possible score, suggesting lost information on student learning and potentially penalizing their teachers. We develop a multi-membership Tobit mixed model to explicitly account for score ceilings in value-added assessment of teacher and school effects. A Monte Carlo expectation-maximization (EM) algorithm is implemented for model estimation. Simulation and analysis of data from the Arizona standardized assessment are presented to demonstrate the practical utility of the proposed methods.


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