Introduction to Multilevel Modeling

 
Introduction to Multilevel Modeling is a two-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: Tests of significance are likely biased and within- and between-group effects are confounded with one another. All of these limitations can be addressed within the multilevel model. In this workshop, we provide an introduction to the application of multilevel models with nested data, including software implementation in SAS, SPSS and Stata.

Instructors: Dan Bauer and Patrick Curran

Dan Bauer is a Professor in 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. He regularly teaches classes and workshops on multilevel modeling. In addition, he has contributed to the research literature on multilevel models, making extensions to address specific problems in the behavioral, social, and health sciences.
Patrick Curran 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 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. His program of research includes an emphasis on multilevel modeling, particularly as applied within a longitudinal setting to capture individual differences in growth over time.
 
 

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