Multilevel Modeling
Replay Access: Expires 1 year after purchase
Original Livestream: June 6-10, 2022
Instructors: Dan Bauer & Patrick Curran
Student: $795
Professional: $995
Multilevel Modeling is a five-day workshop focused on the application and interpretation of multilevel models, also known as hierarchical linear models and mixed models, for the analysis of nested data structures. Nesting can arise from hierarchical data structures (e.g., siblings nested within family; patients nested within therapist), longitudinal data structures (repeated measures nested within individual), or both (repeated measures nested within patient and patient nested within therapist). It is well known that the analysis of nested data structures using traditional general linear models (e.g., ANOVA or regression) is flawed, oftentimes substantially so. Not only are tests of significance likely biased, but many important within-group and between-group relations cannot be evaluated. All of these limitations can be addressed within the multilevel model. In this workshop we provide a comprehensive exploration of multilevel models with topics ranging from introductory to advanced, as described below.
Instructors
Daniel J. Bauer, Ph.D.
Dan Bauer is a Professor and the Director of the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina. He teaches primarily graduate-level courses in statistical methods, for which he has won multiple teaching awards. Read More
Patrick J. Curran, Ph.D.
Patrick Curran is a Professor in the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill. He is dedicated to teaching and disseminating advanced quantitative methods and has won multiple awards for teaching excellence. Read More
Workshop Details
Reviews
In an effort to continually improve our instruction we obtain student evaluations with each course offering. Here is a sample of reviews from prior Multilevel Modeling workshops:
Thank you for such an amazing workshop! I learned so much and cannot wait to dig into my dissertation data!
The concepts and practical applications are hard for me, but in this class I really felt like I’ve had some Eureka moments. It really came together for me. I think that speaks to both of your teaching abilities, the format of the class, and the organization of the materials. I love the dynamic between you two and your teaching styles complement each other well. I had a blast, a really good time, and loved it.
Everything is a strength -- balance between lecture/practical, the pace at which the material is delivered, the course material/resources, etc. Really just everything.
The workshop does a great job of explaining MLM on a conceptual level and provides useful examples to better understand the modeling. The instructors were great at teaching the material and were very open to answering questions.
This workshop strikes a perfect balance between theory and practical applications. I particularly appreciated this as my MLM grad class was several years ago, so this was a refresher and an extension now that I have the data to actually analyze.
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Self-Paced Workshops
Free Introduction to Structural Equation Modeling
Replay Access: 1 year
Recorded: May 11-13, 2022
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Causal Inference
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Latent Class/Cluster Analysis and Mixture Modeling
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Applied Measurement Modeling
Replay Access: 1 year
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Applied Research Design Using Mixed Methods
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Replay Access: 1 year
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Longitudinal Structural Equation Modeling
Replay Access: 1 year
Recorded: May 16-20, 2022
Instructors: Dan Bauer & Patrick Curran
Modern Missing Data Analysis
Replay Access: 1 year
Recorded: June 1-3, 2022
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Applied Qualitative Research
Replay Access: 1 year
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Introduction to Quantitative Meta-Analysis
Replay Access: 1 year
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Analyzing Intensive Longitudinal Data
Replay Access: 1 year
Recorded: June 13-17, 2022
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Machine Learning: Theory and Applications
Replay Access: 1 year
Recorded: May 16-20, 2022
Instructor: Doug Steinley