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.