Segregation is a network-level property such that edges between 
  predefined groups of vertices are relatively less likely. Network homophily 
  is a individual-level tendency to form relations with people who are similar 
  on some attribute (e.g. gender, music taste, social status, etc.). In general
  homophily leads to segregation, but segregation might arise without 
  homophily. This package implements descriptive indices measuring 
  homophily/segregation. It is a computational companion 
  to Bojanowski & Corten (2014) <doi:10.1016/j.socnet.2014.04.001>.

The network structural equation modeling conducts a network 
    statistical analysis on a data frame of coincident observations of 
    multiple continuous variables [1]. 
    It builds a pathway model by exploring a pool of domain knowledge guided 
    candidate statistical relationships between each of the variable pairs, 
    selecting the 'best fit' on the basis of a specific criteria such as 
    adjusted r-squared value.
    This material is based upon work supported by the U.S. National Science 
    Foundation Award EEC-2052776 and EEC-2052662 for the MDS-Rely IUCRC Center, 
    under the NSF Solicitation: 
    NSF 20-570 Industry-University Cooperative Research Centers Program 
    [1] Bruckman, Laura S., Nicholas R. Wheeler, Junheng Ma, Ethan Wang, 
    Carl K. Wang, Ivan Chou, Jiayang Sun, and Roger H. French. (2013) 
    <doi:10.1109/ACCESS.2013.2267611>.

We developed a comprehensive tool that helps with visualization and analysis of networks with the same variables across multiple factor levels. The 'netShiny' contains most of the popular network features such as centrality measures, modularity, and other summary statistics (e.g. clustering coefficient). It also contains known tools to look at the (dis)similarities between two networks, such as pairwise distance measures between networks, set operations on the nodes of the networks, distribution of the weights of the edges and a network representing the difference between two correlation matrices. The package 'netShiny' also contains tools to perform bootstrapping and find clusters in networks. See the 'netShiny' manual for more information, documentation and examples.