Skip to content
No description, website, or topics provided.
HTML R
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
new code
Manual.pdf
Manual_HTML.html
NetworkApp.Rproj
README.md
runapp.R
server.R
ui.R

README.md

READ ME for Shiny Network Application

This Shiny application visualizes a graph structure for a dataset. The user can adjust all features of the visualized graph and download a pdf version of it. Furthermore, centrality analyses will automatically be performed; a centrality table and plot will be visualized in the second and third tab and both can be downloaded. The fourth and fifth tab visualizes the Clustering table and plot; these can also be downloaded. Code for running the application can be found in the runapp.R file.

This application is a project that is under construction, features will be added along the way. If you have any suggestions as to what features are useful to be added, please feel free to contact me at mail[at]jolandakossakowski[dot]eu.

Version 1.0 of this application has now been released. Visit https://jolandakos.shinyapps.io/NetworkApp/ to try it out!

It is also possible to use the app in R by running the following line of R-code: source("https://raw.githubusercontent.com/JolandaKossakowski/NetworkApp/master/runapp.R")

Current available features:

  • General

    • Demo version option that will automatically upload predefined data if chosen
    • The app will automatically detect the correct settings for uploading the data
    • It is possible to select a smaller range of variables than is present in the datafile
    • Control widgets that are needed for a specific estimation method will appear when this estimation method is chosen
  • Network Estimation

    • Add a title
    • Change the graph layout
    • Add node labels (columnames)
    • Use weighted edges
    • Use directed edges
    • Display graph details
    • Change minimum edge weight
    • Change maximum edge weight
    • Change cut-off value
    • Change edge size
    • Change node size
    • Download pdf of graph
    • Upload your own dataset
    • Various network estimation options
    • Option for performing non-paranormal transformation
    • Option for coding missing values
    • Calculate and report the Small-World Index
  • Centrality tab

    • Add second tab with centrality table and plot
    • Download centrality table and plot
    • Change asthetics of centrality plot
    • Choose centrality measures
  • Clustering tab

    • Add third tab with clustering table and plot
    • Download clustering table and plot
    • Change asthetics of clustering plot
    • Choose clustering measures
  • Network Comparison tab

    • Ability to compare two network structures based on the weighted density

Features that will be implemented:

  • Network visualization

    • Enter group specification that will be visualized
    • Add a legend
    • Change node colours
    • Extend functions for more than 1 dataset
  • Centrality tab

    • Add asthetics of centrality plot
    • Add option to sort centrality measures based on value
    • Highlight maximum/minimum values
  • Clustering tab

    • Add asthetics of clustering plot
    • Add option to sort clustering measures based on value
    • Highlight maximum/minimum values
  • Other features

    • Plot that compares centrality measure against clustering measure with median values of both
    • Add possibility to mention which column had participant numbers in them
    • create "busy" notion whilst constructing networks

All features are implemented using the R-package qgraph version 1.3.1.

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.

Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. (2014). State of the aRt personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality.

You can’t perform that action at this time.