Introduction to Network Analysis

December 14-16, 2020
Online Webinar via Zoom
Instructor:
Doug Steinley
Software Demonstrations: R

Clear

Course Description

Introduction to Network Analysis is a three-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). Throughout, we demonstrate visualization techniques for leveraging the true power of network data — understanding how observations are interrelated with each other.

Course Schedule

Start date: December 14, 2020

End date: December 16, 2020

Start time: 10:00 a.m. EDT

End time: 06:00 p.m. EDT

Venue: Zoom Webinar

Email: info@curranbauer.org

Instructor

Doug SteinleyDoug Steinley

Doug Steinley is a Professor in the Department of Psychology at the University of Missouri. His research and teaching focus on multivariate statistical methodology, with a primary interest in cluster analysis (both traditional procedures and more modern mixture modeling techniques) and social network analysis. Dedicated to dissemination, Doug has taught workshops on these and other advanced quantitative methods for many years, joining Curran-Bauer Analytics in 2016. He has also published over 100 peer-reviewed manuscripts, and held funding from the National Institutes of Health, the US Army Research Institute, and the Office of Naval Research. He currently serves as Editor of the flagship methods journal for the American Psychological Association, Psychological Methods. For more details, see his academic web page.

Course Details

Who Should Attend and Software Considerations?

Our workshop is designed for graduate students, post-doctoral fellows, faculty, and research scientists from the behavioral, social, and health sciences.

Software demonstrations will be provided in R (you can download R for free). While it is helpful to have some familiarity with R, this is not necessary. The lectures which constitute the majority of the workshop are software-independent.

The Goals of the Workshop

Our motivating goal is to provide an intense yet enjoyable instructional experience that focuses on a large number of both introductory and advanced topics in network analysis. We strive to strike an equal balance between core concepts of the analytic techniques along with their practical application and interpretation when implemented with real empirical data. Our workshop is designed to provide participants with the materials and instruction needed to both develop a real understanding of network analysis techniques and to be able to thoughtfully apply these procedures to their own data.

Reviews from Past Participants

In an effort to continually improve our instruction we obtain student evaluations with each course offering. Here is a sample of reviews from our prior 2020 online offering of Network Analysis:

The key strengths were the knowledge of the instructor and his enthusiasm for the material. I also thought the materials were clear, quite complete, and the R code demonstrations were very helpful. Overall, I was quite pleased.

Doug provided a comprehensive overview of network analysis, including theory, history, and methods.

One can always learn new techniques reading textbooks and looking for examples on the internet. But, what you don't get is the benefit of experience. Taking this course, you get the tremendous benefit of Doug' experience. Invaluable.

The teacher was clearly an expert in the field. His presentation was interesting and knowledgeable.

I really like having access to the videos. It allowed me to go back through the material and figure out difficult areas or work through elements I didn't fully understand.

Extensive overview of network analysis. The Instructor is really responsive to student questions and tailor towards student needs.

Great systematic overview of Network Analysis, how it works and some of the challenges we are likely to encounter. His experience and knowledge really came through in his discussion.

Doug is clearly an expert in this field and has a strong knowledge about how to apply it to various venues. Thoroughly enjoyed the workshop and I look forward to taking some more.

What is Provided

Doug Steinley will teach the workshop via Zoom. Participants will receive complete PDF copies of the course notes and the computer demonstrations as well as data and code for all examples. The PDFs are not time-limited and may be retained indefinitely but should not be distributed to others without obtaining prior permission.

For examples of our course materials see sample copies of our structural equation modeling lecture notes and associated Mplus demonstration notes, as well as our multilevel modeling lecture notes and SAS software notes.

Interactions with Instructors

Participants can ask text-based questions using a Zoom function that will be monitored by CBA staff and conveyed to the instructor. If a question cannot be answered during lecture, a text response will be provided at a later time.

Connectivity Requirements

Because participants are receiving the stream from Zoom and not broadcasting video images back, the connectivity requirements are minimal. A minimum of 150kbps (kilobytes per second) is required to participate in a video webinar, and this can be wired or wireless. Given typical home internet connections or personal WiFi access, these requirements are quite low. For example, it is recommended that a 3000kbps (or 3mbps, megabytes per second) connection be used to stream a movie on Netflix. A typical WiFi hotspot on a typical cell phone is 20-30mbps, thus any standard internet connection should allow for uninterrupted participation in the webinar. See https://www.speedtest.net/ to evaluate your own connection speed. Note that a typical source of connectivity problems in the home is linking the device to the WiFi broadcast unit, so be certain your device is has uninterrupted lines of site to the wireless modem; see, e.g., https://www.familyhandyman.com/smart-homeowner/9-simple-tips-for-faster-wi-fi/

Daily Schedule

Livestream lectures will begin at 10:00 a.m. and finish at 5:00 p.m. Eastern Time (US) each day. Following the lectures, computer demonstrations in R will be provided from 5:00 p.m. to 6:00 p.m. Eastern Time (US).

There will be 15-minute morning and afternoon breaks and a one hour lunch break, the exact times of which are determined during lecture. Local time zones within which the participant is connected must be adjusted to correspond to Eastern Standard Time.

Availability of Recordings

The live-stream does not have DVR-like controls and thus cannot be paused or rewound during the session itself. However, full recordings of the live-stream will be available to all participants for 14 days following the completion of the workshop. The recordings cannot be saved by the participant and will not be available after the 14-day period.

Technical Support

CBA is not able to provide technical support for end-user issues. As such, participants are fully responsible for connectivity that supports the live-stream of audio and video. Information will be provided about the minimum required bandwidth and methods for testing connectivity. However, in the low probability that a participant is not able to connect, there will be access to the recorded sessions for 14 days following the completion of the workshop.

Tuition Reduction Opportunities

We offer reduced-price registrations for graduate students who are actively enrolled in a recognized masters or doctoral training program. No application is necessary to qualify for the student tuition rates; simply choose the student rate when beginning the registration process at the top of the page. Confirmation of student status may be requested at a later time.

Support for Junior Scholars from Under-Represented Groups

We are fortunate to have the opportunity to work in collaboration with the Society of Multivariate Experimental Psychology (SMEP) to provide a limited number of financial awards to students from under-represented groups to attend methodological workshops. These awards are made to qualifying students and post doctoral fellows with available funds of up to $1000 per student. Please see Support for Students from Underrepresented Groups to Attend Methodological Workshops for full details on both of these sources of support.

Cancellation Policy

Curran-Bauer Analytics will fully refund registration fees, minus transaction fees, for cancellations made with one week or more notice prior to the event. Registration fees are non-refundable if a cancellation is made less than one week before the event.

Syllabus

Chapter 1. Basics of Network Analysis
1.1 Historical Overview
1.2 Representation of Networks as Graphs, Sets, and Matrices
1.3 Types of Networks
1.4 Measuring and Collecting Network Data

Chapter 2. Identifying the Most Important Actors/Elements in a Network
2.1 Short Introduction to Graph Theory
2.2 Properties of Networks
2.3 Identifying the Most Central Actors: Centrality Measures

Chapter 3. Visualizing Network Relationships
3.1 Foundations of Visualization Methods
3.2 Visualizing Relationships between Actors

Chapter 4. Finding Members of Networks with Similar Traits
4.1 Clustering and Graph Partitioning
4.2 Finding Densely Linked Sets of Actors: Community Detection

Chapter 5. Brain Network Analysis
5.1 Introduction to Brain Networks
5.2 Connecting Network Terminology to Brain Structure
5.3 Small World Networks and Network Economy
5.4 Null Models for Connectivity Networks

Chapter 6. Psychometric Network Models: Modeling Relationships Among Item Responses
6.1 Motivating Application: Psychiatric Symptom Networks
6.2 Models for Continuous and Binary Data
6.3 Estimation Approaches
6.4 Advanced Topics in a Rapidly Evolving Area

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