The traditional approach to measuring segregation is based upon descriptive, non-model-based indices. A recently proposed alternative is multilevel modeling. The authors further develop the argument for a multilevel modeling approach by first describing and expanding upon its notable advantages, which include an ability to model segregation at a…

In this article, we discuss the effect of removing the independence assumptions between the residuals in two-level random effect models. We first consider removing the independence between the Level 2 residuals and instead assume that the vector of all residuals at the cluster level follows a general multivariate normal distribution. We…

The Programme for International Student Assessment comparative study of reading performance among 15-year-olds is reanalyzed using statistical procedures that allow the full complexity of the data structures to be explored. The article extends existing multilevel factor analysis and structural equation models and shows how this can extract richer…

Presents a method for handling educational data in which students belong to more than one unit at a given level, but there is missing information on the identification of the units to which students belong. The method, which involves setting up a cross-classified model, is illustrated with longitudinal data on students' progress in English. (SLD)

An efficient procedure is described for specifying and estimating parameters of general mixed models that contain both hierarchical and crossed random factors. The approach, using a model formulated for purely hierarchical structured data, is illustrated for the continuous response linear model with extensions to generalized linear, nonlinear, and…