Network Analysis

May 11-15, 2020
Online Webinar via Zoom
Instructor: Doug Steinley
Software Demonstrations: R

Note that this workshop will be held the same week as our Structural Equation Modeling workshop

Register for the Workshop

Registration is now closed

ACCESS INFORMATION

Participants who registered and paid for this class by 5/4 received an email with access information on 5/4 at approximately 5 pm EST.  If you did not receive an email and believe you should have, please first check your spam folder and then email us if you are unable to find it.

Participants who register or complete payment after 5/4 will receive an email with access information upon completing payment.  This is not an automated email, so it may arrive a few hours after your registration.

Network Analysis is a five-day workshop taught by Doug Steinley that focuses on the application and interpretation of techniques for modeling connections between observations (e.g., actors) within a network. Examples include social networks among peers, connectivity networks in fMRI data, symptom networks in diagnostic data, and management networks within the workplace. In this workshop we first introduce the basic concepts of network analysis, such as centrality measures, and the descriptive, structural analysis of network data. After covering these foundations, we discuss special considerations for two burgeoning areas of application: brain network analysis for examining connectivity and psychometric network models for examining the structure of item responses (e.g., symptom networks). Last, we explore how we can use exponential random graph models (ERGMs) to obtain inferential tests of specific hypotheses about network characteristics in both cross-sectional and longitudinal data. Throughout, we demonstrate visualization techniques for leveraging the true power of network data — understanding how observations are interrelated with each other.

Please contact us either via email or by phone (984.999.0636) if you need any additional information or have any further questions.