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This course teaches models for multilevel nested data that arise in nested designs. Traditional methods, such as OLS regression, are not appropriate in this setting as they fail to model the complex correlational structure that is induced by these designs. This class explores how to develop and fit a set of models for nested designs through multilevel regression, also known as mixed effects models or hierarchical linear models.

Course #:
APSTA-GE 2042
Credits:
3

Professors

Professor Marc Scott

Marc Scott

Professor of Applied Statistics; Co-Director of PRIISM