Network Training

These presentations and data were presented as part of the 2020 ISTSS Pre-Meeting Institute:
A Practical Introduction to Network Modeling in R: From Cross-Sectional Models to Short-Term Dynamics

Recordings of the PMI are available from ISTSS (link to be presented soon).

Please feel feel free to share, ask questions, or provide feedback to Matthew.Price@uvm.edu

Presentations

Slides from the different sections of the PMI. Please feel free to use (and thank you to those who helped contribute).

Introduction to Network Analysis
Cross Sectional Network Analysis
Longitudinal Network Analysis
Wrap-Up and Considerations

Sample Data Sets

These datasets are used to run the examples in scripts provided below. All of the day is simulated from actual datasets obtained from previously presented studies. They are meant to be used for practice only.

Cross-Sectional Data

Sample of 500 individuals with PCL-5 data. Based on data from: https://pubmed.ncbi.nlm.nih.gov/30502492/

Physical Assault Data and Disaster Data

Sample of individuals with PCL-5 data who were exposed to either a natural disaster of physical assault. Meant to be used for a network comparison test. Based on data from: https://pubmed.ncbi.nlm.nih.gov/30502492/

Longitudinal Data

Sample of individuals with 5 symptoms from the PCL-5 and pain data collected longitudinally for 30 days. Based on data from: https://pubmed.ncbi.nlm.nih.gov/31730736/

Practice Scripts

Introduction to R

A brief script to introduce a user to working with R and running a basic network analysis. Best if used with the Cross-sectional data from above.

Cross Sectional Network Script

A script to walk through conducting a cross-sectional network. Best if used with the Cross-sectional data from above. The disaster and physical assault data from above are used for the network comparison test.

Longitudinal Data

A script to walk through conducting a cross-sectional network.

Large Objects

Several of the operations in the prior script take a long time to compute. You can load these files and place them in your working directory to avoid having to run them on your own (although it is certainly great practice to do so!).

References

Here is an archive of papers that were referenced in the above slides.
References.zip