Chapter 1: Introduction to Multilevel Modeling Methods: Pedagogy and Context

“Hierarchies abound.” That is how we started our first edited volume for this series, more than a decade ago (O’Connell & McCoach, 2008). Since that time, the science of multilevel modeling has continued to advance, with development of new theory and applications, and improved algorithms and access to software capable of fitting multilevel models. This new volume is a collection of work by researchers dedicated to furthering the use of multilevel analyses in education, health, and the social/behavioral sciences. Underpinning these efforts is the recognition that data are often correlated in ways that affect our inferences about relationships among variables of interest, and accommodating this correlation assures better understanding of educational and social phenomena. This correlation can arise with hierarchical or clustered data, such as observations on students within different schools, or longitudinal data, where repeated measurements are clustered within individuals.