Multiple outputation for the analysis of longitudinal data subject to irregular observation. (13th December 2015)

• Record Type: Journal Article
• Authors: Pullenayegum, Eleanor M.
• Is Part Of: Statistics in medicine. Volume 35:Number 11(2016)
• Page Start: 1800
• Page End: 1818
• Publication Date: 2015-12-13
• Subjects: longitudinal data -- joint models -- inverse‐intensity weighting; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.6829
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : Observational cohort studies often feature longitudinal data subject to irregular observation. Moreover, the timings of observations may be associated with the underlying disease process and must thus be accounted for when analysing the data. This paper suggests that multiple outputation, which consists of repeatedly discarding excess observations, may be a helpful way of approaching the problem. Multiple outputation was designed for clustered data where observations within a cluster are exchangeable; an adaptation for longitudinal data subject to irregular observation is proposed. We show how multiple outputation can be used to expand the range of models that can be fitted to irregular longitudinal data. Copyright © 2015 John Wiley & Sons, Ltd.