As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…

This paper extends single-level missing data methods to efficient estimation of a "Q"-level nested hierarchical general linear model given ignorable missing data with a general missing pattern at any of the "Q" levels. The key idea is to reexpress a desired hierarchical model as the joint distribution of all variables including…

Applied early adolescent researchers often sample students (Level 1) from within classrooms (Level 2) that are nested within schools (Level 3), resulting in data that requires multilevel modeling analysis to avoid Type 1 errors. Although several articles have been published to assist researchers with analyzing sample data nested at two levels, few…