STATS 761 Mixed Models

Below description edited in year: 2013

Points: 15

Prereqs: STATS 301

Credit: Examination 60% and assignments 40%

For Advice: Katya (Kathy) Ruggiero (Email: k.ruggiero@auckland.ac.nz | extn: 89938), Patricia Metcalf (Email: p.metcalf@auckland.ac.nz | extn: 82317)

Taught: Second Semester City

Website: STATS 761 website

STATS 761 will describe statistical techniques for the analysis of epidemiological data with an emphasis on mixed modelling. This course will also describe mixed modelling techniques for the analysis of data arising from small-scale designed experiments, addressing questions such as “What are the effects of ocean acidification on gene expression in sea urchins?”. A common feature of some of the datasets in this course is that they have multiple sources of random variation, which cannot be directly measured. Both theory and practice will be covered. 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.

Topics studied include: Linear mixed models, generalised linear and generalised linear mixed models; and restricted maximum likelihood for unbalanced designs. Analyses will include multicentre trials (random effects models), and repeated measures data (covariance pattern and random coefficient models).

Disclaimer:
Although every reasonable effort is made to ensure accuracy, this information for the course year (2013), 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.