Statistical Methods Course Description
Overview: This summer institute is designed primarily for researchers who are interested in conducting social network research, particularly those who are embarking upon it for the first time.
Morning sessions will consist primarily of lectures and class discussions. Afternoon sessions will be dedicated to lab demonstrations and activities designed to help participants become users of social network methods and software. Participants are not required but encouraged to bring their own complete network data. The Friday afternoon session will be reserved for consulting on individual projects.
Survey a variety of approaches to collecting and analyzing network data at single and multiple points in time using R software. Topics include basic statistics and visualization, network regression/QAP, exponential random graph models (ERGMs), and stochastic actor-oriented models (RSiena). The workshop will consist of a mixture of classroom teaching and hands-on computer work. As such, this is a great introduction to R for anyone! Network data will be provided for the lab activities and participants will conduct some type of analysis every day. This is an applied course that will take you from novice to proficient in 5 days!
Instructors: Leslie Echols & Michael D. Siciliano
Leslie is an Assistant Professor in the Department of Psychology at Missouri State University. She holds a Ph.D. in education with a specialization in human development and psychology from University of California, Los Angeles. She also hold a M.S. in education from City University of New York. She is a former elementary education teacher and currently studies peer relations in the school context. Specifically, much of her research investigates the role of school ethnic composition and scheduling practices on friendship and victimization among classmates and other peers.
Michael is an Assistant Professor in the Department of Public Administration at the University of Illinois at Chicago (UIC). He holds a Ph.D. in public policy and public administration from the University of Pittsburgh and a master’s in public policy analysis from Carnegie Mellon University. Michael’s work investigates the factors influencing network formation as well as the effect of social structure on individual and collective behavior, decision-making, and performance. Michael has taught network analysis training courses and workshops for the Public Management Research Association, the Midwest Association for Public Opinion Research (MAPOR), the Science of Team Science Conference, the Center for Disaster Management at the University of Pittsburgh, and the Center for Clinical and Translational Science at UIC.
Software and Computer Support
This summer institute is designed primarily for researchers who are interested in conducting social network research, particularly those who are embarking upon it for the first time. The course will provide information on data collection and visualization, and will focus on the use of exponential random graph models (ERGMs; cross-sectional network analysis) and stochastic actor-oriented models (Siena, longitudinal network analysis) with in the R programming environment. R novices are welcome!
Below are links to course files for those who enrolled in the course. Please download these files onto your computer before the first day of the course. The files are password protected to respect the intellectual property rights of the instructors. By using your login information you agree not to share your login information or the content protected by it.
After May 1st: Click Here to Access Introduction to Social Network Analysis using R and RSiena