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Multilevel Modeling

6. Multilevel Data Structures

Hierarchies

It is well known that once groupings are created (consisting of individuals), even if their origins are essentially ‘random,’ individuals end up being influenced by their group membership. Such groupings can be spatial (e.g., areas) or non-spatial (e.g., communities). Hierarchies are one way of representing the dependent or correlated nature of the relationship between individuals and their groups. Thus, for instance, we can conceptualize a two-level structure of many level-1 units (e.g., individuals) nested within fewer level-2 groups (e.g., neighborhoods/places) as illustrated in Figure 2. Since individual outcomes are anticipated as being dependent upon the neighborhoods in which they live, responses within a neighborhood are more alike than different. When dependency is anticipated in the ‘population’ or ‘universe,’ they represent population-based or naturally occurring hierarchies.

Figure 2

Figure of two level structure as described in text.

Subramanian, S., Jones, K., et al. (2003) Multilevel methods for public health research. In: I. Kawachi and L. Berkman (Eds.). Neighborhoods and Health. New York: Oxford Press. 65-111.