To solve the network stability problem, I ran spinglass for four times (My network is too big for more runs). I calculated the contingency table among all results and selected the meaningful intersection of all results. I lost a few false negative nodes in this way, but the core of each module will be relatively stable.

]]>In your example, you used qgraph( graph = “cor”) to create a correlation network. I am wondering if there is any particular reason that you create a graph with qgraph instead of using functions in the igraph package, for example, “graph_from_adjacency_matrix()” function.

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