In school-based randomized control trials (RCTs), a common design is to follow student cohorts over time. For such designs, education researchers usually focus on the place-based (PB) impact parameter, which is estimated using data collected on all students enrolled in the study schools at each data collection point. A potential problem with this…

It is often assumed that a vertical scale is necessary when value-added models depend upon the gain scores of students across two or more points in time. This article examines the conditions under which the scale transformations associated with the vertical scaling process would be expected to have a significant impact on normative interpretations…

Test-based accountability as well as value-added asessments and much experimental and quasi-experimental research in education rely on achievement tests to measure student skills and knowledge. Yet, we know little regarding fundamental properties of these tests, an important example being the extent of measurement error and its implications for…

The impact of uncertainty about item parameters on test information functions is investigated. The information function of a test is one of the most important tools in item response theory (IRT). Inaccuracy in the estimation of test information can have substantial consequences on data analyses based on IRT. In this article, the major part (called…

Using longitudinal data for an entire state from 2004 to 2008, this article describes the results from an empirical investigation of the persistence of value-added school effects on student achievement in reading and math. It shows that when schools are the principal units of analysis rather than teachers, the persistence of estimated school…

In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…

This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response theory (IRT) to a latent variable model with covariates…

The authors propose a strategy for studying the effects of time-varying instructional treatments on repeatedly observed student achievement. This approach responds to three challenges: (a) The yearly reallocation of students to classrooms and teachers creates a complex structure of dependence among responses; (b) a child's learning outcome under a…