Comparing different sedation medications using generalized estimating equations approach

Abstract

Generalized estimating equations (GEE) provide an applicable approach to modelling repeated and clustered data that are often encountered in medical application. This approach is very useful especially when response variables are correlated and categorical, covariates are time-depended, there are a large number explanatory variables and missing data. In this study, using this approach we focus on modelling repeated sedation measurements obtained during magnetic resonance imaging (MRI) and computerized tomography (CT) for children.