STATS 768 Longitudinal data analysis

Below description edited in year: 2017

Points: 15

Credit: Final exam 60%, and assignments 40%

For Advice: Patricia Metcalf (Email: p.metcalf@auckland.ac.nz | extn: 82317)

Taught: Second Semester City

STATS 768 describes mixed models, also known as hierarchical models or multilevel models, a data analysis approach that extends regression by incorporating models for the unexplained variation and correlation in residuals. Mixed models have many applications in applied statistics. They are important for the modelling of repeated measurements, and part of the course will focus on their use in the analysis of epidemiological data. Exploration and regression modelling of longitudinal and clustered data, especially in the sciences: this includes mixed models, marginal models, dropout, and causal inference. Students will be expected to program in SAS and to be able to interpret the resulting output. Examples of SAS code will be given in the lecture notes and explained.

Disclaimer:
Although every reasonable effort is made to ensure accuracy, this information for the course year (2017), is provided as a general guide only for students and is subject to alteration. All students enrolling at the University of Auckland must consult its official document, the University of Auckland Calendar, to ensure that they are aware of and comply with all regulations, requirements and policies.