Mixed Model Methods
Fixed effects, random effects, repeated measures, nonindependent data, general covariance structures, estimation methods.
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
 PrerequisitesSTAT 535
Course Outcomes: 

STAT 537

Students will be able to explain, apply, evaluate, and perform different implements of mixed models

Explain the Difference

Explain the difference between fixed and random effects as implemented in the mixed model

Apply Mixed Models

Appropriately apply mixed models to deal with nonindependent data and variety of covariance structures

Evaluate the Fit

Evaluate the fit of the mixed model using Choleski residuals

Perform Analyzes

Perform analyzes of mixed models using both SAS and R

Perform Bayesian Analysis

Perform full Bayesian analysis of mixed models using Bayesian software