Courses Details
BIOSTAT595: Applied Longitudinal Analysis Using R
- Graduate level
- Residential and Online MPH and Online MS
- This is a first year course for Online students
- Fall term(s) for residential students; Fall term(s) for online MPH students; term(s) for online MS students.
- 2 credit hour(s) for residential students; 2 credit hour(s) for online MPH students; 2 credit hour(s) for online MS students;
- Instructor(s): Masotti, Maria (Residential); Zawistowski, Matt (Online MPH); Zawistowski, Matt (Online MS);
- Prerequisites: Biostat 501, Biostat 591, Biostat 592
- Description: This course provides an overview of statistical methods for analyzing correlated data produced by longitudinal measurements taken over time. Topics include study design, exploratory data analysis techniques and linear mixed effects regression models. This course provides practical concepts and hands-on R computing skills to perform longitudinal data analysis.
- Learning Objectives: 1. Identify causes and patterns of correlated outcomes in health data 2. Perform exploratory data analysis of longitudinal outcomes 3. Fit linear mixed effects regression models 4. Interpret and perform hypothesis testing of regression parameters for mixed models
| Department | Program | Degree | Competency | Specific course(s) that allow assessment | Population and Health Sciences | MPH | Compare population health indicators across subpopulations, time, and data sources | PUBHLTH515, BIOSTAT592, EPID590, EPID592, EPID643, BIOSTAT595, BIOSTAT501 |
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