Clustering is a phenomenon commonly observed across social science research--students are clustered in classrooms, individuals in households, and companies within industrial sectors, to name but a few examples. This book presents an elementary and systematic introduction to modeling of between-cluster variation, how results are best interpreted, and computational methods for estimation. The book addresses many important issues in the social sciences that can be best described in terms of variation sources and patterns, such as temporal, between-person, and geographical variation. By providing a balanced presentation of the advantages and limitations of these methods, the author has provided an introduction to the subject that will be of great utility to statisticians and students concentrating on social science data analysis.