Prof Jouni Kuha

This course is available on the MPA in Data Science for Public Policy, 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 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.

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

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).

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

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

• 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).

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