 What Are Error Rates for Classifying Teacher and School Performance Using Value-Added Models?Peter Z. Schochet and Hanley S. Chiang Journal of Educational and Behavioral Statistics, 2013, vol. 38, issue 2, 142-171 Abstract: This article addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using a realistic performance measurement system scheme based on hypothesis testing, the authors develop error rate formulas based on ordinary least squares and Empirical Bayes estimators. Empirical results suggest that value-added estimates are likely to be noisy using the amount of data that are typically used in practice. Type I and II error rates for comparing a teacher’s performance to the average are likely to be about 25% with 3 years of data and 35% with 1 year of data. Corresponding error rates for overall false positive and negative errors are 10% and 20%, respectively. Lower error rates can be achieved if schools are the performance unit. The results suggest that policymakers must carefully consider likely system error rates when using value-added estimates to make high-stakes decisions regarding educators. Keywords: value-added models; performance measurement systems; student learning gains; false positive and negative error rates (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:38:y:2013:i:2:p:142-171 Access Statistics for this article More articles in Journal of Educational and Behavioral Statistics |
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