March 1, 2004

An Analysis of School District Data Using Value-Added Methodology

Authors:
Damian Betebenner
This paper is an examination of student assessment data using multi-level analysis methods often referred to as “value-added” models. The analyses performed provide measures of “effectiveness” for both teachers and schools. The purpose of the paper is to examine the residuals derived from the model for teachers and schools (i.e., their “value-added” scores) and to examine their relation to demographic variables at the classroom and school level. Three models are examined: the basic variance components model, the random intercepts model, and a model including demographic covariates. Those interpreting the results should be aware of the likelihood of model misspecification in contexts where value-added measures are derived. These measures are a function of the model and much care must be taken to rule out the possibility of model misspecification.
Betebenner, D. (2004). An analysis of school district data using value-added methodology (CSE Report 622). Los Angeles: University of California, Los Angeles, National Center for Research on Evaluation, Standards, and Student Testing (CRESST).|Betebenner, D. (2004). An analysis of school district data using value-added methodology (CSE Report 622). Los Angeles: University of California, Los Angeles, National Center for Research on Evaluation, Standards, and Student Testing (CRESST).
This is a staging environment