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A Correlated Random Effects Model for Nonignorable Missing Data in Value-Added Assessment of Teacher Effects


Abstract Value-added models (VAMs) are used by many states to assess contributions of individual teachers and schools to students' academic growth. The generalized persistence VAM, one of the most flexible in the literature, estimates the ``value added'' by individual teachers to their students' current and future test scores by employing a mixed model with a longitudinal database of test scores. There is concern, however, that missing values that are common in the longitudinal student scores can bias value-added assessments, especially when the models serve as a basis for personnel decisions -- such as promoting or dismissing teachers -- as they are being used in some states. Certain types of missing data require that the VAM be mod... (more)
Created Date 2012
Contributor Karl, Andrew Thomas (Author) / Lohr, Sharon L (Advisor) / Yang, Yan (Advisor) / Kao, Ming-Hung (Committee member) / Montgomery, Douglas C (Committee member) / Wilson, Jeffrey R (Committee member) / Arizona State University (Publisher)
Subject Statistics
Type Doctoral Dissertation
Extent 141 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Ph.D. Mathematics 2012
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis