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SemNeT (version 1.4.4)

compare_nets: Plots Networks for Comparison

Description

Uses qgraph to plot networks. Accepts any number of networks and will organize the plots in the number of side-by-side columns using the heuristic of taking the square root of the number of input and rounding down to the nearest integer (i.e., floor(sqrt(length(input)))).

Examples

  • 3 networks: 1 x 3

  • 6 networks: 2 x 3

  • 9 networks: 3 x 3

Usage

compare_nets(
  ...,
  title,
  config,
  placement = c("match", "default"),
  weighted = FALSE,
  qgraph.args = list()
)

Value

Plots networks using qgraph

Arguments

...

Matrices or data frames of network adjacency matrices

title

List. Characters denoting titles of plots

config

Character. Defaults to "spring" See qgraph for more options

placement

Character. How should nodes be placed when comparing groups? Defaults to "default"

  • "match" places nodes in the same position for all networks

  • "default" places nodes in the default config positions

weighted

Boolean. Should networks be plotted with weights? Defaults to FALSE. Set to TRUE to plot networks with weights corresponding to association strength. Often, unweighted networks are more aesthetically representational of the networks

qgraph.args

List. An argument list to be passed onto qgraph. See qgraph for possible arguments

Author

Alexander Christensen <alexpaulchristensen@gmail.com>

References

Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48, 1-18.

Jones, P. J. (2019). networktools: Tools for Identifying Important Nodes in Networks. R package version 1.2.1.

Jones, P. J., Mair, P., & McNally, R. (2018). Visualizing psychological networks: A tutorial in R. Frontiers in Psychology, 9, 1742.

Examples

Run this code
# Simulate Datasets
one <- sim.fluency(10)
two <- sim.fluency(10)

# Compute similarity matrix
cos1 <- similarity(one, method = "cosine")
cos2 <- similarity(two, method = "cosine")

# Compute networks
net1 <- TMFG(cos1)
net2 <- TMFG(cos2)

# Compare networks
compare_nets(net1, net2, title = list("One", "Two"), config = "spring")

# Change edge colors
compare_nets(net1, net2, title = list("One", "Two"),
config = "spring", qgraph.args = list(edge.color = "blue"))

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