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Livestream Seminar

Multilevel Modeling of Categorical Outcomes

A 4-Day Livestream Seminar Taught by

Donald Hedeker
Course Dates:

Monday, June 27, 2022 –
Thursday, June 30, 2022

Schedule:

10:30am-12:30pm ET (New York time): Live session via Zoom
1:30pm-3:00pm ET: Live session via Zoom

Multilevel models are increasingly used for analysis of clustered and longitudinal data, and methods for continuous outcomes are commonly used and applied. However, many research studies have non-normal outcomes, for example, outcomes that are dichotomous, ordinal, or nominal. Although methods for such non-normal outcomes have been available for quite some time, they are perhaps not as routinely applied as models for continuous outcomes.

This workshop will focus on analysis of dichotomous, ordinal and nominal multilevel outcomes. Both clustered and longitudinal data will be considered, and the following models will be described: multilevel logistic regression for dichotomous outcomes, multilevel logistic regression for nominal outcomes, and multilevel proportional odds and non-proportional odds models for ordinal outcomes. The latter models are useful because the proportional odds assumption of equal covariate effects across the cumulative logits of the model is often inconsistent with the data.

Starting June 27, we are offering this seminar as a 4-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. Participants are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if they are unable to attend at the scheduled time.

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously. 

Closed captioning is available for all live and recorded sessions.

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“It helped me to understand the complex issues related to multilevel models.”

“It was a great experience to take part in this course. It helped me to understand the complex issues related to multilevel models. The eagerness of the tutor to answer all the questions was on an exceptionally high level. I strongly recommend this course to anyone interested in multilevel models.”

Szymon Wójcik

University of Lodz

“I really liked his ability to cover a lot of material and do it clearly.”

“Professor Hedeker is excellent. I really liked his ability to cover a lot of material and do it clearly. This is a weak area of mine and he helped fill in many of the gaps in my own understanding.”

Richard Williams

University of Notre Dame

“Dr. Hedeker put very rich contents into this class."  

“Dr. Hedeker put very rich contents into this class. Students are allowed to raise questions at any time through the class. This helps students to catch the important points in a timely manner and get through the learning easily.”

Qin Liu

The Wistar Institute

“... an in-depth discussion of the theory, fitting, and interpretation of multilevel modeling for non-normal data."

“This class offers an in-depth discussion of the theory, fitting, and interpretation of multilevel modeling for non-normal data that does not seem to exist elsewhere. Don puts together and delivers arguably the best short course I’ve ever taken. This course is well worth the time and money.”

Amy Hughes

University of Texas

“... many tips, tricks, nuances, and insights communicated from Don’s many years of experience...”

“I found Don’s course very helpful for advanced as well as intermediate analysis of categorical data in clustered structures. There were many tips, tricks, nuances, and insights communicated from Don’s many years of experience with categorical data problems. I am taking away many helpful strategies for approaching my ongoing projects.”

Andrea Howard

Carleton University