CHL5222H Position Description
The course introduces statistical methods to analyze correlated data commonly arising from applied outcome research and health sciences. The course focuses on the analysis of longitudinal and repeated measure data with the emphasis on the applications and the interpretation of the analytic results. Examples are extensively used to illustrate concepts and implemented using the software R. Students who are interested in the course can review the article Statistical Approaches to Longitudinal Data Analysis in Neurodegenerative Diseases: Huntington’s Disease as a Model to have a more granular overview of the course materials.
Instructors: Aya Mitani
Qualifications:
TA must have a mature understanding of all topics covered in the course. This includes a very strong knowledge of correlated data analysis, longitudinal data analysis (GLM, GEE, mixed effects models), and the R statistical software. In general, TA should have strong data analysis and statistical skills.
Duties:
a) Consultation with the course supervisor, b) Marking/grading problem sets, c) Calculating, recording, and tabulating grades, d) Weekly office hours and answering emails for student questions, e) Prepare and give one lecture (optional, only if TA wants to have the opportunity to teach a class)
Relevant Criterion:
Previous experience is the more relevant criterion than the need to acquire experience in respect of this posted position.