Professor Fiona Steele COL 7.08

This course is available on the 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.

A knowledge of probability and statistical theory, including linear regression and logistic regression.

A practical introduction to methods for the analysis of repeated measures data, including continuous and binary outcomes. Topics include: longitudinal study designs, (random effects) growth curve models, marginal models, dynamic (autoregressive) models, latent class models, and multiprocess models for multivariate outcomes. The course will have an applied emphasis with weekly computer classes using appropriate software (e.g. Stata).

20 hours of lectures and 10 hours of computer workshops in the LT. 2 hours of lectures in the ST.

Coursework assigned fortnightly and returned to students with comments/feedback during the computer sessions.

Singer JD, Willett JB. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford University Press (2003). (Part I only).
Hedeker D, Gibbons RD. Longitudinal Data Analysis. Hoboken, New Jersey: John Wiley & Sons, Inc. (2006).

Exam (100%, duration: 2 hours) in the main exam period.