Dr Jouni Kuha COL 8.02

Primarily for MSc Statistics, MSc Statistics (Research), MSc Statistics (Financial Statistics), MSc Statistics (Financial Statistics) (Research), and MSc Social Research Methods.

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., individuals nested within households or geographical areas) and longitudinal data (eg 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).

Lectures: 20 LT, computer classes: five two-hour sessions LT.

Coursework assigned fortnightly and returned to students with comments/feedback during the lab sessions.

T Snijders & R Bosker Multilevel Analysis: an Introduction to Basic and Advanced Multilevel Modelling, Sage (1999);
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).

Also recommended are: A Skrondal & S Rabe-Hesketh, Generalized Latent Variable Modeling: Multilevel, Longitudinal and Structural Equation Models, Chapman & Hall (2004); H Goldstein, Multilevel Statistical Models, Arnold (2003); S W Raudenbush & A S Bryk, Hierarchical Linear Models: Applications and Data Analysis Methods, Sage (2002); G Verbeke & G Molenberghs, Linear Mixed Models for Longitudinal Data, Springer (2000); E Demidenko, Mixed Models, Wiley (2004).

A two-hour written examination in the ST (100%).