Introduction to Multilevel Modeling

$475.00$595.00

December 2-4, 2020
Livestream via Zoom
Instructors: Dan Bauer and Patrick Curran
Software Demonstrations: R, SAS, SPSS, and Stata

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Category: Livestream, Workshops

Introduction to Multilevel Modeling is a three-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, including estimation of main effects and interactions, decomposing within- and between-group effects, and the analysis of repeated measures data.

Instructors

Dan BauerDaniel 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 teaching awards from the University of North Carolina and from the American Psychological Association.  Endeavoring to make advanced statistical techniques more accessible, Dan has spent the last 15 years developing and teaching workshops on a variety of topics in both the United States and abroad, including multilevel modeling, mixture modeling, longitudinal data analysis, structural equation modeling, latent curve analysis, missing data analysis, measurement, and integrative data analysis. His research interests lie at the intersection of quantitative and developmental psychology, particularly the development of problem and health-related behaviors over childhood and adolescence. He has published over 65 scientific papers, served as Associate Editor for Psychological Methods, currently serves on the editorial boards of several journals, and has reviewed grants for the National Science Foundation, National Institutes of Health, and the Institute of Educational Sciences. He received an early career award from the American Psychological Association in 2009. For more details, see his academic web page.

Patrick CurranPatrick 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. Patrick has dedicated much of his career to the teaching and dissemination of advanced quantitative methods and has won teaching awards from UNC and from the American Psychological Association. Over the past 20 years Patrick has taught over 50 national and international workshops on structural equation modeling, multilevel modeling, latent curve analysis, longitudinal data analysis, and general linear modeling. He draws on experiences from his own program of research on high risk child development to guide and inform his quantitative teaching. Patrick’s program of research is primarily focused on the development and evaluation of statistical models of change over time, particularly as applied to studies of adolescent substance use. He has published over 70 scientific papers and chapters and has co-authored a text book on latent curve modeling with Ken Bollen. Patrick has served as Associate Editor for Psychological Methods and currently serves on the editorial boards of seven scientific journals. For more details, see his academic web page.

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 our prior 2020 online offering of Multilevel Modeling:

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 -- the 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.

I appreciate that both Dan and Patrick explained everything in a very understandable way, regardless of your statistical knowledge and background. The examples provided throughout the lectures were extremely helpful too.

The instructors are highly skilled in clearly conveying complex concepts in very accessible manner. Coverage of the material on the topic was extremely thorough and useful. The SAS afternoon sessions were fantastic.

Clarity! Excellent instructors were able to scaffold the material in a helpful, comprehensible manner. I was very impressed with how well everything worked via Zoom, particularly since this was the first entirely-online season.

Such an excellent training opportunity! After taking this course, I feel much more confident in my ability to develop models for my dissertation.

The ability of both presenters to communicate important statistical and research concepts in clear, understandable language. After enduring a number of undergraduate and graduate level statistics courses this one was the first that felt accessible.

Really, really helpful!! I am a graduate student and managed to convince my department to let me use my travel funds this year to enroll in this class. The lectures and demos are so refreshingly clear, I would have paid out of pocket!

This was a fantastic workshop. I am a second-year graduate student and have only taken one semester of statistics so far, and found that Patrick and Dan presented this challenging material in an accessible, fun and engaging way.

The applied, practical focus and many real-world examples were key strengths. Also, the notes for the syntax were phenomenal! I really appreciate the time taken to annotate the code so well.

This training was the best thing to happen to me during my dissertation - a life saver! I am infinitely grateful.

Both instructors are SO knowledgeable. I have taken courses on MLM before and you still offered a lot more. I also learned some tricks (e.g., entering the group means when centering) that were so helpful and clarified materials I have struggled with.

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