Suspended in 2025/26
ST442 Half Unit
Longitudinal Data Analysis
This information is for the 2025/26 session.
Course Convenor
Prof Fiona Steele
Availability
This course is available on the MPA in Data Science for Public Policy, MRes in Management (Marketing), MSc in Health Data 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 freely available as an outside option to students on other programmes where regulations permit. It does not require permission. This course uses controlled access as part of the course selection process. How to apply: Priority is given to Department of Statistics students, including students on the MSc in Health Data Science, and those with the course listed in their programme regulations.
Students should check that they meet the pre-requisites in the course guide before applying but do not need to provide a written statement.
Deadline for application: Due to the nature of the method of application, interested students should apply as soon as possible after the opening selection and no later than 10.00am on Friday 27 September 2024.
Course lecturers will aim to make initial offers to students on LSE For You by Friday 27 September.
For queries contact: Stats-Msc@lse.ac.uk
This course has a limited number of places (it is controlled access). In previous years we have been able to provide places for all students that apply but that may not continue to be the case.
Requisites
Additional requisites:
A knowledge of probability and statistical theory, including linear regression and logistic regression.
Please log into moodle.lse.ac.uk and self-enrol in the 'R for Statistics Pre-sessional Course
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 measurements, (random effects) growth curve models, marginal models, missing data, latent class models, models for binary data and dynamic (autoregressive) models. The course will have an applied emphasis with fortnightly computer classes using R.
Teaching
20 hours of lectures and 10 hours of computer workshops in the Winter Term.
This course has a reading week in Week 6 of Winter Term.
Students are required to install R on their own laptops for use in the computer workshops.
Formative assessment
Coursework assigned fortnightly and returned to students via Moodle with feedback.
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: 120 Minutes in the Spring exam period
Key facts
Department: Statistics
Course Study Period: Winter Term
Unit value: Half unit
FHEQ Level: Level 7
CEFR Level: Null
Total students 2024/25: 5
Average class size 2024/25: 5
Controlled access 2024/25: NoCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Problem solving
- Application of numeracy skills