Multivariate Multilevel Value-Added Modeling: Constructing a Teacher Effectiveness Composite

Abstract

This simulation study presents a justification for evaluating teacher effectiveness with a multivariate multilevel model. It was hypothesized that the multivariate model leads to more precise effectiveness estimates when compared to separate univariate multilevel models. Then, this study investigated combining the multiple effectiveness estimates that are produced by the multivariate multilevel model and produced by separate univariate multilevel models. Given that the models could produce significantly different effectiveness estimates, it was hypothesized that the composites formed from the results of the multivariate multilevel model differ from the composites formed from the results of the separate univariate models in terms of bias. The correlations between the composites from the different models were very high, providing no evidence that the model choice was impactful. Also, the differences in bias and fit were slight. While the findings do not really support a claim for the use of the more complex multivariate model over the univariate models, the increased theoretical validity from adding outcomes to the VAM does.