Multi-level Modeling (Glasgow, Scotland, UK)


We will begin by examining the basics of a two-level model. From there we will proceed to the analysis of other hierarchical structures with several levels and then onto complex non-hierarchical population structures, including cross-classified and multiple membership models. We look at examples for the use of multilevel models with longitudinal data and social network data. Throughout the course, we will look at examples based on substantive research questions, and will include hands-on computing sessions to practice the application of the various approaches. The main software used is R - and also MLwiN with R, through the packages MLwiN, as will be explained. We will look other R packages that enable more complex multilevel models to be fitted, including R2WinBUGS and R2OpenBUGS - which work with WinBUGS and OpenBUGS respectively, and also the MCMCglmm package.

Prerequisites: Participants should be familiar with basic statistical methods including OLS regression analysis. Familiarity with the basics of logistic regression would also be an advantage, though I will briefly review this, prior to giving details of the multilevel logistic regression model.

Software: The main software used is R, including the use of MLwiN and WinBUGS with R.

Fee: Members = $1500; Non-members = $2800

Tags: multilevel models, multi-level, hierarchical linear models

Course Sections