ABSTRACT
For society, network capital conveys resources, confirms identity, influences behavior, and reinforces integrative links between individuals, households, and groups. Multilevel analysis is just starting to be used in sociology to integrate "nested data" into a single statistical model, such as occurs with residents in neighborhoods, children in schools, nation-states in world systems, individuals and ties in personal networks. Multilevel analysis shows that network characteristics do not affect the relationship of tie strength to support. In the loosely coupled world of contemporary personal communities, strong ties function somewhat independently of the networks in which they are embedded. This multilevel approach has two advantages. First, it provides estimates of the effects of variables at the individual, tie, and network levels while controlling for effects at the other levels. Second, it captures elusive interactive effects of network capital by examining how the composition and structure of networks affect individual and tie supportiveness.
