ST411 Half Unit
Generalised Linear Modelling and Survival Analysis
This information is for the 2025/26 session.
Course Convenor
Dr Anastasia Kakou
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 Data Science, MSc in Health Data Science, MSc in Marketing, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.
Requisites
Additional requisites:
Mathematics to the level of Mathematical Methods (MA100) and probability to the level of Probability, Distribution Theory and Inference (ST202). Some knowledge of linear regression.
Course content
An introduction to the theory and application of generalised linear models for the analysis of continuous, categorical and count data, and regression models for survival data. Topics include: general theory of regression and generalised linear models, linear regression, logistic regression for binary data, models for ordered and unordered (nominal) responses, log-linear models for count data, and models for survival (duration) data. The R software package will be used in computer workshops.
Teaching
20 hours of computer workshops and 20 hours of lectures in the Autumn Term.
This course has a reading week in Week 6 of Autumn Term.
Formative assessment
Answers to questions based on theoretical and data analysis exercises can be submitted for formative feedback.
Indicative reading
- Dobson, A.J. & Barnett, A.G. (2002) An Introduction to Generalised Linear Modelling. 2nd edition. Chapman & Hall.
- McCullagh, P. & Nelder, J.A. (1989) Generalized Linear Models. 2nd edition. Chapman & Hall.
- Agresti, A. (2015) Foundations of Linear and Generalized Linear Models. Wiley [Available as electronic resource from LSE library].
- Hosmer, D.W. & Lemeshow, S. (1999) Applied Survival Analysis, Regression Modeling of Time-to-Event Data. Wiley.
- Long, J.S. and Freese, J. (2006) Regression Models for Categorical Dependent Variables Using Stata. 2nd edition. Stata Press.
Assessment
Exam (100%), duration: 120 Minutes in the Spring exam period
Key facts
Department: Statistics
Course Study Period: Autumn Term
Unit value: Half unit
FHEQ Level: Level 7
CEFR Level: Null
Total students 2024/25: 26
Average class size 2024/25: 13
Controlled access 2024/25: YesCourse 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