The interaction of size and density with graph-level indices

The size and density of graphs interact powerfully and subtly with other graph-level indices (GLIs), thereby complicating their interpretation. Here we examine these interactions by plotting changes in the distributions of several popular graph measures across graphs of varying sizes and densities. We provide a generalized framework for hypothesis testing as a means of controlling for size and density effects, and apply this method to several well-known sets of social network data; implications of our findings for methodology and substantive theory are discussed. (C) 1999 Elsevier Science B.V. All rights reserved.