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STAT 727

THEORY AND METHODS OF LONGITUDINAL DATA ANALYSIS

3 credits.

Theory and methods of fundamental statistical models for the analysis of longitudinal data, including repeated measures analysis of variance, linear mixed models, generalized linear mixed models, and generalized estimating equations. Introduction of how to implement these methods in statistical softwares such as in R and/or SAS, within the context of appropriate statistical models and carry out and interpret analyses.

Prerequisites & course information

Requisites: STAT 610 Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2025 Learning Outcomes: 1. Analyze longitudinal data in a variety of settings and with a variety of outcome variables Audience: Graduate 2. Apply statistical methods in fitting longitudinal data models for addressing scientific questions Audience: Graduate 3. Perform longitudinal data analyses in statistical softwares such as R and/or SAS Audience: Graduate 4. Interpret and communicate the scientific meanings of the results to both statisticians and non-statisticians (such as clinicians and scientists) Audience: Graduate Learning Outcomes: 1. Analyze longitudinal data in a variety of settings and with a variety of outcome variables Audience: Graduate 2. Apply statistical methods in fitting longitudinal data models for addressing scientific questions Audience: Graduate 3. Perform longitudinal data analyses in statistical softwares such as R and/or SAS Audience: Graduate 4. Interpret and communicate the scientific meanings of the results to both statisticians and non-statisticians (such as clinicians and scientists) Audience: Graduate

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