ST416      Half Unit
Multilevel Modelling

This information is for the 2022/23 session.

Teacher responsible

Professor Irini Moustaki

Availability

This course is available on the MSc in Health Data Science, MSc in Social Research Methods, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan), 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 with permission as an outside option to students on other programmes where regulations permit.

Priority is given to students from the Departments of Statistics and Methodology, and those with the course listed in their programme regulations.

Pre-requisites

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

Course content

A practical introduction to multilevel modelling with applications in social research. This course deals with the analysis of data from hierarchically structured populations (e.g. student nested within classes, individuals nested within households or geographical areas) and longitudinal data (e.g. repeated measurements of individuals in a panel survey). Multilevel (random-effects) extensions of standard statistical techniques, including multiple linear regression and logistic regression, will be considered. The course will have an applied emphasis with computer sessions using appropriate software (e.g. Stata).

Teaching

This course will be delivered through a combination of lectures and computer classes totalling a minimum of 30 hours in Lent Term. This course includes a reading week in Week 6 of Lent Term.

Formative coursework

Coursework assigned fortnightly and returned to students via Moodle with comments/feedback before the computer lab sessions.

Indicative reading

  • T Snijders & R Bosker Multilevel Analysis: an Introduction to Basic and Advanced Multilevel Modelling, Sage (2011, 2nd edition);
  • S Rabe-Hesketh & A Skrondal, Multilevel and Longitudinal Modeling using Stata, (Third Edition), Volume I: Continuous responses (plus Chapter 10 from Volume II, which is available free on the publisher's website). Stata Press (2012);
  • H Goldstein, Multilevel Statistical Models, Arnold (2003, 3rd edition);
  • S W Raudenbush & A S Bryk, Hierarchical Linear Models: Applications and Data Analysis Methods, Sage (2002).

Assessment

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

Student performance results

(2018/19 - 2020/21 combined)

Classification % of students
Distinction 40
Merit 30.8
Pass 26.2
Fail 3.1

Key facts

Department: Statistics

Total students 2021/22: 20

Average class size 2021/22: 20

Controlled access 2021/22: Yes

Lecture capture used 2021/22: Yes (LT)

Value: Half Unit

Guidelines for interpreting course guide information

Course 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

  • Self-management
  • Team working
  • Problem solving
  • Communication
  • Application of numeracy skills
  • Specialist skills