Victoria C. Morckel
University of Michigan-Flint

Multilevel models are important to use when data are nested. To demonstrate this point, an example is given where the probability of a house being abandoned is predicted using house- and neighborhood-level variables. The example illustrates the types of findings that are possible when different spatial scales are carefully considered. The final model indicates that for stable neighborhoods, house-level characteristics have a greater impact on the probability than do neighborhood-level characteristics; however, for more distressed neighborhoods, neighborhood characteristics matter more. Without the use of multilevel modeling techniques, this relationship might not have been found.