Given the natural hierarchical structure in school-setting data, multilevel modeling (MLM) has been widely employed in education research using a number of different statistical software packages. The purpose of this article is to review a recent feature of Stat-JR, the statistical analysis assistants (SAAs) embedded in Stat-JR (Version 1.0.5),…

Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…

A continuing challenge for the education system is how to evaluate the wider outcomes of schools. Wider measures of success--such as citizenship or lifelong learning--influence each other and emerge over time from complex interactions between students, teachers and leaders, and the wider community. Unless methods are found to evaluate these…

Background/Context: Most reforms in elementary education rely on teacher learning and improved instruction to increase student learning. This study increases our understanding of which types of professional development effectively change teaching practice in ways that boost student achievement. Purpose/Objective/Research Question/Focus of Study:…

This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…