In contrast to the multigroup models illustrated in Chapters 7, 8, and 9 in which analyses were based on data representing different populations, the multigroup model examined in this chapter focuses on a single population that is hierarchically structured. Such models are termed multilevel (MLV) models because the data lend themselves to more than one level of analyses. Most commonly, examples of hierarchically structured data are (a) students nested within schools, (b) patients nested within clinics, (c) employees nested within firms or corporations, and (d) children and adults nested within families, among others. Such hierarchical structures are often termed nested data or clustered data. In essence, however, hierarchical structures may involve more than two levels of analysis. For example, building upon these earlier examples, data could be extended to include schools nested within districts, and districts nested within states; or employees nested within departments, departments nested within business organizations, organizations nested within regions, and so on.