Multilevel analysis of personal networks as dependent variables

In this paper, it is shown that multilevel methods are particularly well-su ited for the analysis of relations in personal networks and the changes in these relations. Justice is done to the hierarchical nested structure of th e data and the resulting dependence between observations "within egos". Mul tilevel techniques can also give more specific insight on why personal netw orks change: they allow to distinguish between. the influence of individual and of tie characteristics on the stability of personal networks as a whol e and of specific ties within a personal network. This is illustrated by an application to changes in networks of four Dutch samples experiencing diff erent life events. (C) 1999 Elsevier Science B.V. All rights reserved.