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A Priori Analysis Of Error And Bias In Value-Added Models, Matthew Lavery

Electronic Theses and Dissertations

Over the past 20 years, value-added models (VAMs) have become increasingly popular in educational assessment and accountability policies because of the sophisticated statistical controls these models use to purportedly isolate the effect of a single teacher on the learning gains of his or her students. The present research uses a Monte Carlo simulation study design in order to investigate whether VAMs are able to provide accurate estimates of teacher effectiveness when all assumptions are met and to determine how robust the models are to endogenous peer effects and nonrandom assignment of students to classroom. The researcher generates three years of …