ST442      Half Unit
Longitudinal Data Analysis

This information is for the 2017/18 session.

Teacher responsible

Prof Fiona Steele COL 7.08

Availability

This course is compulsory on the MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). 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.

Amended paper details (11/07/2017 NB)

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.

Student performance results

(2013/14 - 2015/16 combined)

Classification % of students
Distinction 25
Merit 25
Pass 45.8
Fail 4.2

Key facts

Department: Statistics

Total students 2016/17: 14

Average class size 2016/17: 16

Controlled access 2016/17: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of numeracy skills