ST416 Half Unit
Multilevel Modelling
This information is for the 2020/21 session.
Teacher responsible
Professor Irini Moustaki
Availability
This course is available on the 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.
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 or all of this teaching may be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos. 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
(2016/17 - 2018/19 combined)
| Classification | % of students |
|---|---|
| Distinction | 46.3 |
| Merit | 17.9 |
| Pass | 17.9 |
| Fail | 17.9 |
Important information in response to COVID-19
Please note that during 2020/21 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 situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of 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 2019/20: 23
Average class size 2019/20: 22
Controlled access 2019/20: No
Value: Half Unit
Personal development skills
- Self-management
- Team working
- Problem solving
- Application of numeracy skills
- Specialist skills
