Use of generalized estimating equations in a trial in influenza to explore treatment effects over time

For trials with repeated measurements of outcome, analyses often focus on univariate outcomes, such as analysis of summary measures or of the last on-treatment observation. Methods which model the whole data set provide a rich source of approaches to analysis. For continuous data, mixed-effect modelling is increasingly used. For binary and categorical data, models based on use of generalized estimating equations account for intra-subject correlation and allow exploration of the time course of response, as well as providing a useful way to account for missing data, when such data can be maintained as missing in the analysis. The utility of this approach is illustrated by an example from a trial in influenza. Copyright © 2004 John Wiley & Sons Ltd.