2017 SNH Workshop

2017 Social Networks and Health Workshop: May 22nd through May 26th

Schedule:

Monday, May 22nd Tuesday, May 23rd Wednesday, May 24th Thursday, May 25th Friday, May 26th
Fellows mini-conference Descriptive Statistics (Molly Copeland) Regression with networks- ego networks/ randomization (Brian Aronson) Inference for networks- dyad model overview (Alex Volfovsky) Siena models for selection & influence (David Schaefer)
Community detection (Peter Mucha)
LAB- Descriptive Statistics (Jon Morgan) Open Lab Inference for networks- ERGMs (Zack Almquist) LAB- Siena models (David Schaefer)
Welcome/ introductions (Jim Moody) IRB Discussion (Kathie Harris) Respondent-driven sampling (RDS) (Ashton Verdery) Causal inference (Weihua An) Social Networks & Health: History and Open Problems (Jim Moody)
Data Collection (Jim Moody) Network Canvas (Michelle Birkett) Applications of networks- diffusion (Jake Fisher) LAB- ERGM (Zack Almquist)
Visualization (Jim Moody)
LAB- Data Management (Jake Fisher) LAB- Visualization (Jim Moody) LAB- Diffusion Simulation (Jake Fisher) Open Lab

 

Workshop Materials:

Data & Coding Resources

Day 1-

Fellows mini-conference (Recordings unavailable)

  • “Racial/ethnic differences in medical mistrust among breast cancer patients: What are the roles of network characteristics?” Yamile Molina, University of Illinois- Chicago (Slides)
  • “Using Social Network Analysis to Inform HIV Prevention and Treatment Efforts in Tanzania” Marta Mulawa, Duke University (Slides)
  • “Partner or Perish? Public Health Delivery Systems & Cancer Screenings for the Uninsured under the ACA” Jennie Law, Rockefeller College (Slides)
  • “Examining the Dynamic Spread of Marijuana Use in a Social Network with Community Structure” Albert Burgess-Hull, University of Wisconsin-Madison (Slides)

Welcome/Introductions (Jim Moody, Duke University)

Data Collection (Jim Moody, Duke University)

LAB- Data Management (Jake Fisher, Duke University)

 

Day 2-

Descriptive Statistics (Molly Copeland, Duke University)

Community Detection (Peter Mucha, UNC Chapel Hill)

LAB- Descriptive Statistics (Jon Morgan, Duke University)

IRB Discussion (Kathie Harris, Add Health Director)

Network Canvas (Michelle Birkett, Northwester University)

Visualization (Jim Moody, Duke University)

LAB- Visualization (Jim Moody, Duke University)

 

Day 3-

Regression with networks- ego-networks/randomization (Brian Aronson, Duke University)

Respondent-driven sampling (RDS) (Ashton Verdery, Penn State University)

Applications of networks- diffusion (Jake Fisher, Duke University)

LAB- Diffusion Simulation (Jake Fisher, Duke University)

 

Day 4-

Inference for networks- Dyad model overview (Alex Volfovsky, Duke University)

Inference for networks- ERGMs (Zack Almquist, University of Minnesota)

Causal inference (Weihua An, Indiana University)

LAB- ERGM (Zack Almquist, University of Minnesota)

 

Day 5-

Siena models for selection & influence (David Schaefer, Arizona State University)

LAB- Siena models (David Schaefer, Arizona State University)

Social Networks & Health: History and Open Problems (Jim Moody, Duke University)