Hierarchical Linear Models II: Special Topics

Instructor(s):

• Stephen Raudenbush, Sociology, University of Chicago
• Guanglei Hong, Human Development and Applied Psychology, University of Toronto

This is a second course in hierarchical linear models. Individuals who enroll should have taken the ICPSR course Hierarchical Linear Models I: Introduction or its equivalent, and have experience using HLM research techniques. This course will consider four special topics: generalized hierarchical linear models, including nonlinear models for binary, count, ordinal, and multinomial outcomes; latent variable models, including random effects as latent variables, random coefficients as predictors, and embedding measurement models in HLM; multivariate models for growth, with consideration of a variety of alternative covariance structures including compound symmetry, autoregressive structures, and heterogeneous level-1 variance; and models for dyads, with consideration of cross-sectional models for matched pairs and longitudinal models for dyads changing over time.

Dates:  July 6-9 

Fee:  Member: $1600; Non-member: $3600

This course is limited to 20 participants.