Modeling sparse longitudinal data in early neurodevelopment

• Published in: NeuroImage (Orlando, Fla.) Vol. 237; p. 118079
• Main Authors: Chen, Yaqing, Dubey, Paromita, Müller, Hans-Georg, Bruchhage, Muriel, Wang, Jane-Ling, Deoni, Sean
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.08.2021; Elsevier Limited; Elsevier
• Subjects: Age; Anatomy; Brain architecture; Brain development percentiles; Brain-for-age growth chart; Cerebrospinal fluid; Child development; Children; Cognitive ability; Concurrent regression modeling; Data analysis; Functional principal components; Individual developmental trajectory reconstruction; Longitudinal studies; Neuroimaging; Population; Substantia alba; Substantia grisea; Whole brain MRI; Functional principal components; Concurrent regression modeling; Brain development percentiles; Whole brain MRI; Individual developmental trajectory reconstruction; Brain-for-age growth chart

•Obtaining mean trend and modes of variation for sparse longitudinal neuroimaging data.•Reconstructing individual smooth trajectories using PACE approach.•The PACE method outperforms established random-effects models for trajectory recovery.•Nonparametric estimation of dynamic quantiles to construct...