ÐÓ°ÉÂÛ̳

 

ST416      Half Unit
Multilevel Modelling

This information is for the 2021/22 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) (ÐÓ°ÉÂÛ̳ 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 computer classes and lectures totalling a minimum of 30 hours across  Lent Term. This year, some of this teaching may be delivered through a combination of classes and virtual lectures delivered synchronously. 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.

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.

Student performance results

(2017/18 - 2019/20 combined)

Classification % of students
Distinction 44.3
Merit 22.9
Pass 21.4
Fail 11.4

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Statistics

Total students 2020/21: 25

Average class size 2020/21: 25

Controlled access 2020/21: Yes

Value: Half Unit

Personal development skills

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