Tools & resources
A practical introduction to network modeling in R
From cross-sectional models to short-term dynamics. These materials were presented at the 2020 ISTSS Pre-Meeting Institute. Recordings are available from ISTSS.
Please feel free to share, ask questions, or provide feedback to Matthew.Price@uvm.edu.
Presentations
Slides from each section of the PMI. Please feel free to use them — and thank you to those who helped contribute.
1 · Introduction to network analysisSlides
2 · Cross-sectional network analysisSlides
3 · Longitudinal (time-varying) network analysisSlides
4 · Wrap-up and considerationsSlides
Sample data sets
Used to run the examples in the scripts below. All data are simulated from previously published studies and are meant for practice only.
Cross-sectional dataSample of 500 individuals with PCL-5 data. Based on PMID 30502492.
Physical assault dataPCL-5 data from individuals exposed to physical assault; for the network comparison test.
Disaster dataPCL-5 data from individuals exposed to a natural disaster; for the network comparison test.
Longitudinal data5 PCL-5 symptoms and pain collected daily for 30 days. Based on PMID 31730736.
Practice scripts
Introduction to RWorking with R and running a basic network. Best with the cross-sectional data.
Cross-sectional network scriptCross-sectional networks plus the network comparison test (disaster vs. physical assault).
Time-varying network scriptWalks through estimating networks from the longitudinal data.
Large objectsPre-computed results for the slowest steps — place in your working directory to skip long runs.
Note: the time-varying script and large-objects links currently point to the same file.