APPLYING A SPATIOTEMPORAL MODEL FOR LONGITUDINAL CARDIAC IMAGING DATA

摘要

Longitudinal imaging studies have both spatial and temporal correlation among the multiple outcome measurements from a subject. Statistical methods of analysis must properly account for this autocorrelation. In this work we discuss how a linear model with a separable parametric correlation structure could be used to analyze data from such a study. The goal of this paper is to provide an easily understood description of how such a model works and discuss how it can be applied to real data. Model assumptions are discussed and the process of selecting a working correlation structure is thoroughly discussed. The steps necessitating collaboration between statistical and scientific investigators have been highlighted, as have considerations for missing data or uneven follow-up.