Prof Fiona Steele COL 7.12

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), MSc in Statistics (Research), MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). This course is available as an outside option to students on other programmes where regulations permit.

Amended paper details (11/07/2017 NB)

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, models for two measurements, (random effects) growth curve models, marginal models, missing data, latent class models and dynamic (autoregressive) models. The course will have an applied emphasis with fortnightly computer classes using the Stata software.

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

Week 6 will be used as a reading week.

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

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.

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