School value-added models are widely applied to study, monitor, and hold schools to account for school differences in student learning. The traditional model is a mixed-effects linear regression of student current achievement on student prior achievement, background characteristics, and a school random intercept effect. The latter is referred to…

Empirical Bayes's (EB) estimation has become a popular procedure used to calculate teacher value added, often as a way to make imprecise estimates more reliable. In this article, we review the theory of EB estimation and use simulated and real student achievement data to study the ability of EB estimators to properly rank teachers. We compare the…

Investigations of the effects of schools (or teachers) on student achievement focus on either (1) individual school effects, such as value-added analyses, or (2) school-type effects, such as comparisons of charter and public schools. Controlling for school composition by including student covariates is critical for valid estimation of either kind…

Regression methods can locate student test scores in a conditional distribution, given past scores. This article contrasts and clarifies two approaches to describing these locations in terms of readily interpretable percentile ranks or "conditional status percentile ranks." The first is Betebenner's quantile regression approach that results in…

Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

Illustrates and compares three alternative procedures to adjust significance levels for multiplicity: (1) the traditional Bonferroni technique; (2) a sequential Bonferroni technique; and (3) a sequential approach to control the false discovery rate proposed by Y. Benjamini and Y. Hochberg (1995). Explains advantages of the Benjamini and Hochberg…

An analytical approach was employed to compare sensitivity of causal effect estimates with different assumptions on treatment noncompliance and non-response behaviors. The core of this approach is to fully clarify bias mechanisms of considered models and to connect these models based on common parameters. Focusing on intention-to-treat analysis,…