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.
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