ST755 - Advanced Analysis of Variance and Mixed models
- Prerequisites: ST702, ST732
- Term & Frequency: Not scheduled at this time.
- Student Audience: PhD students interested in mixed model methodology
- Credit: 3 credits
- Recent Texts: None
- Recent Instructors: Daowen Zhang
- Background and Goals: This special topic covers theories of linear mixed models and generalized linear mixed models, including the estimation and inference of the fixed effects, random effects and variance components; it also covers variance components tests in mixed model, connection of mixed models and nonparametric regression and methods for relaxing random effects distribution.
- Content: Linear mixed models, BLUEs/BLUPs, large-sample and small-sample inference for fixed effects, estimation and inference of variance components; Generalized linear mixed models, Laplace approximation, PQL, bias correction for fixed effects and variance components; Variance components testing; Mixed effect representation of smoothing spline estimate of a nonparametric function; Conditional inference for mixed models, flexible distribution of random effects in mixed models.
- Alternatives: None
- Subsequent Courses: None
S1 2017 Sections:
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