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Abstract Details

Activity Number: 73
Type: Contributed
Date/Time: Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Education
Abstract - #306308
Title: Binning by Quantile Applied to Value-Added Models in Education
Author(s): Pamela Fellers*+
Companies: University of Nebraska
Address: 340 Hardin Hall North, Lincoln, NE, 68583-0963, United States
Keywords: value-added modeling ; generalized linear mixed model ; Assessment ; binning
Abstract:

Value-added models (VAM) are prevalently used as a tool to assess teacher and school contributions to students' academic growth. There is increasing interest in using VAM to assess the impact of professional development programs. However, the data available often do not meet the technical requirements of current VAM. One common challenge occurs when available student achievement data come from multiple assessments over time. Binning by quantile is one possible approach for dealing with this problem. This talk will provide a description of the binning by quantile method along with simulation study results to highlight the behavior and computational issues of this method as compared to other proposed methods.


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