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Categorical Data Analysis - Online Course

A 4-Day Livestream Seminar Taught by

Trenton Mize
Course Dates: Ask about upcoming dates
Schedule: All sessions are held live via Zoom. All times are ET (New York time).

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

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Many—perhaps even most— behavioral, health, and social science questions include outcome variables that are categorical. E.g. Which political candidate will win the next election? How does a parent’s social class influence children’s educational attainment? How many publications does it take to receive tenure? Do men or women drink more alcoholic drinks? Is a vaccine effective at preventing disease? Answering these—and countless other—questions cannot be adequately accomplished via the linear regression model and instead require the more advanced techniques covered extensively in this seminar.

Categorical Data Analysis is a seminar in applied statistics that primarily deals with regression models in which the dependent variable is binary, nominal, ordinal, or count. Many common statistical issues including interpretation of coefficients, calculation of predictions, testing of interaction effects, testing for mediation or other cross-model comparisons, and assessing model fit, require a different approach for models with categorical dependent variables. The focus of the course is on interpretation and learning to deal with the complications introduced by the nonlinearity of the models.

Specific models considered include: probit and logit for binary outcomes; ordered logit/probit and the generalized ordered logit model for ordinal outcomes; multinomial logit for nominal outcomes; and Poisson, negative binomial, and zero inflated models for counts.

Starting June 14, 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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"I learned a ton and I am already rethinking ways to use these materials in my research..."

“The pacing and format were really good. We covered a lot of detailed information very quickly and the instructor provided a really effective organization for the materials, moving from theory through examples and practice problems. Dr. Mize was also very responsive to questions and willing to work with students to adapt the material to their needs, which I really appreciated. I learned a ton and I am already rethinking ways to use these materials in my research and improve the way I teach this information in my courses.” 

Jessie Huff

University of Nebraska at Omaha

"He makes things I first thought were complex very simple and easy to understand."

“Very practical with real empirical illustrations and examples. Lots of supporting and reference materials. Dr. Mize was teaching from his own published materials which has an added advantage of him been able to excellently demonstrate and discuss vividly what he was teaching to my understanding. He makes things I first thought were complex very simple and easy to understand. He is really good at what he does.”

Lawrence Ado-Kofie

The University of Manchester, UK

"...this course was very helpful in understanding the underlying logic of working with categorical data..."

“I thought I had a pretty good handle on categorical data analysis (CDA), but this course was very helpful in understanding the underlying logic of working with categorical data and considerations that need to be made. It was very informative and demonstrated the use and application of current advances in CDA. I particularly benefitted from and appreciated the Stata .do files that accompanied the lecture slides and examples, and the lab as well. The instructor also went above and beyond by providing practical ways for presenting/reporting the output of the techniques and approaches described. Excellent course!”

Wura Jacobs

California State University, Stanislaus