Jul 24, 2024  
2023-2024 Graduate Catalog 
    
2023-2024 Graduate Catalog [ARCHIVED CATALOG]

Add to Portfolio (opens a new window)

STAT 8450:Multilevel Statistical Modeling

3 Credit Hours
Prerequisite: Admission to a KSU PhD Program
Data often have a structure that is nested or hierarchical. For example, when investigating student outcomes, we need to consider that students are nested inside classrooms that are in turn nested inside schools. Clustered data violate the assumption of independence of error terms expected of the general linear model family, which includes ANOVA and regression. Multilevel models allow us to analyze data where observations are nested and not independent, correctly modeling correlated errors and avoiding biased standard errors and parameter estimates. This course will focus on how to use multilevel (hierarchical) models for dealing with nested data. We will discuss common topics in multilevel modeling, including sample size requirements, centering decisions, assumptions, and slopes and intercepts as fixed and random effects. Our focus will be on two and three level nested models, as well as growth modeling.



Add to Portfolio (opens a new window)