A Comparison of Modelling Strategies for Value-Added Analyses of Educational Data

Abstract

Modelling strategies for value-added multilevel models are examined. These types of models typically include an endogenous variable and this causes difficulties for the standard estimation techniques that are commonly used to analyse multilevel models. Two alternative estimation strategies are proposed- one using an instrumental variable approach and the other using a Bayesian analysis as available through the BUGS software. We conclude that that the approach offered by the BUGS software has advantages over more classical estimation methods.