Test Measurement Error and Inference from Value-Added Models

Cory Koedel, Rebecca Leatherman and Eric Parsons ()
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Rebecca Leatherman: Department of Economics, University of Missouri-Columbia, https://economics.missouri.edu/

No 1201, Working Papers from Department of Economics, University of Missouri

Abstract: It is widely known that standardized tests are noisy measures of student learning, but value added models (VAMs) rarely take direct account of measurement error in student test scores. We examine the extent to which modifying VAMs to include information about test measurement error (TME) can improve inference. Our analysis is divided into two parts – one based on simulated data and the other based on administrative micro data from Missouri. In the simulations we control the data generating process, which ensures that we obtain accurate TME metrics with which to modify our value-added models. In the real-data portion of our analysis we use estimates of TME provided by a major test publisher. We find that inference from VAMs is improved by making simple TME adjustments to the models. This is a notable result because the improvement can be had at zero cost.

Keywords: value added models; value added; teacher value added; test measurement error; teacher evaluation (search for similar items in EconPapers)
JEL-codes: I20 (search for similar items in EconPapers)
Pages: 31 pgs.
Date: 2012-01-30
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (17)

Published in The B.E. Journal of Economic Analysis and Policy 2012

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Journal Article: Test Measurement Error and Inference from Value-Added Models (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:umc:wpaper:1201

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