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

Andrew T. Karl, Yan Yang and Sharon L. Lohr
Additional contact information
Andrew T. Karl: Adsurgo LLC
Yan Yang: Arizona State University
Sharon L. Lohr: Westat

Journal of Educational and Behavioral Statistics, 2013, vol. 38, issue 6, 577-603

Abstract: Value-added models have been widely used to assess the contributions of individual teachers and schools to students’ academic growth based on longitudinal student achievement outcomes. There is concern, however, that ignoring the presence of missing values, which are common in longitudinal studies, can bias teachers’ value-added scores. In this article, a flexible correlated random effects model is developed that jointly models the student responses and the student missing data indicators. Both the student responses and the missing data mechanism depend on latent teacher effects as well as latent student effects, and the correlation between the sets of random effects adjusts teachers’ value-added scores for informative missing data. The methods are illustrated with data from calculus classes at a large public university and with data from an elementary school district.

Keywords: generalized linear mixed model; joint model; missing not at random; multiple membership model (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:38:y:2013:i:6:p:577-603

DOI: 10.3102/1076998613494819

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