ST442 Half Unit
Longitudinal Data Analysis
This information is for the 2015/16 session.
Teacher responsible
Prof Fiona Steele COL 7.08
Availability
This course is available on the MSc in Inequalities and Social Science, MSc in Social Research Methods, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available as an outside option to students on other programmes where regulations permit.
Pre-requisites
A knowledge of probability and statistical theory, including linear regression and logistic regression.
Course content
A practical introduction to methods for the analysis of repeated measures data, including continuous and binary outcomes. Topics include: longitudinal study designs, models for two measures, (random effects) growth curve models, marginal models, dynamic (autoregressive) models, latent class models, and models for multivariate outcomes. The course will have an applied emphasis with fortnightly computer classes using the Stata software.
Teaching
20 hours of lectures and 10 hours of computer workshops in the LT.
Week 6 will be used as a reading week.
Formative coursework
Coursework assigned fortnightly and returned to students with comments/feedback during the computer sessions.
Indicative reading
Singer JD, Willett JB. (2003) Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford University Press. (Part I only).
Rabe-Hesketh S, Skrondal A. (2012) Multilevel and Longitudinal Modeling Using Stata, Third Edition. Volume I: Continuous Responses. College Station, Texas: Stata Press.
Hedeker D, Gibbons RD. (2006) Longitudinal Data Analysis. Hoboken, New Jersey: John Wiley & Sons, Inc.
Assessment
Exam (100%, duration: 2 hours) in the main exam period.
Key facts
Department: Statistics
Total students 2014/15: 9
Average class size 2014/15: 10
Controlled access 2014/15: No
Value: Half Unit
Personal development skills
- Problem solving
- Application of numeracy skills