Advanced Multilevel Modeling

3 credits · Graduate School

The main objective of Advanced Multilevel Modeling is to build on foundational knowledge about multilevel modeling (MLM) to expand students’ repertoire of methods for handling clustered data. Topics will vary from semester to semester according to student preferences, but may include some mix of: multilevel mediation and moderation, assessing agreement-within-group, multilevel SEM, models for ecological momentary assessment (EMA) data, dyadic data models, cross-classified / multiple-membership (CCMM) models, partial nesting, MLM for categorical outcomes, nonlinear MLMs, generalized additive mixed models (GAMMs), diagnostics, collinearity, substantive applications of MLM, the history of MLM, power analysis and sample size, spatial models, model selection, and location-scale models. [3]