  The article presents several approaches to the blockmodeling of multilevel
network data. Multilevel network data consist of networks that are measured on
at least two levels (e.g. between organizations and people) and information on
ties between those levels (e.g. information on which people are members of
which organizations). Several approaches will be considered: a separate
analysis of the levels; transforming all networks to one level and
blockmodeling on this level using information from all levels; and a truly
multilevel approach where all levels and ties among them are modeled at the
same time. Advantages and disadvantages of these approaches will be discussed.
