Lancaster-Warwick-Stirling node

A one day workshop by Don Hedeker, University of Illinois at Chicago, to be held on Wednesday 10^th November at the Postgraduate Statistics Centre, Lancaster University

Registration    ¦    How to get to Lancaster University    ¦    Short biography of Don Hedeker | course materials

In this 1-day workshop, attendees will learn about the use of multilevel or mixed models for analysis of longitudinal categorical data. The focus will be on data analysis, with direct application illustrated using standard statistical software (i.e., SAS). Some of the topics to be covered include: (1) multilevel models for dichotomous outcomes, and (2) multilevel models for ordinal and nominal outcomes.

1) As dichotomous outcomes are common in many research areas, multilevel models for dichotomous data are extremely important. In particular, multilevel logistic regression models will be presented and described. Attention will be paid to the "subject-specific" interpretation of the parameters in these models, as well as techniques for deriving "population averaged" estimates.

2) Extensions of the multilevel logistic model for ordinal and nominal outcomes will be presented.  In particular, both proportional odds and non-proportional odds models will be discussed and compared.  The latter models are useful because the proportional odds assumption of equal covariate effects across the cumulative logits of the model is often unreasonable.  Instead, allowing the covariates to have varying influences across the cumulative logits of the ordinal responses provides a very flexible approach to the modeling of ordinal outcomes.

Hedeker, D. & Gibbons, R. D. (2006). Longitudinal Data Analysis. Wiley, New York