BSTA 668 - Longitudinal Data Analysis

Units: 2
Introduction to the principles and methods for the analysis of longitudinal data, repeated measures, and correlated outcomes, including the unbalanced and incomplete data that are characteristic of observational longitudinal data. Generalized estimating equations and generalized linear mixed models.

Prerequisites: STAT 631 and STAT 632.
Possible Instructional Methods: On-ground.
Grading: A-F grading only.
Student Learning Outcomes - Upon successful completion of this course students will be able to:

Apply biostatistical methodology to data to (a) produce descriptive statistics, probability models, and visual displays (b) select probability distributions to implement statistical inference (estimation and hypothesis testing), and (c) critique biostatistical models for uncertainty, likelihood, modeling and error analysis at the Master’s level.
Evaluate practical problems arising in biostatistics to select and formulate models for solutions using these methodologies.
Select and generate biostatistical software output and evaluate the results appropriately.
Derive basic theory, explain biostatistical concepts, and clearly communicate analytical results to others.