ArticleNeuroImage2014
FMEM: functional mixed effects modeling for the analysis of longitudinal white matter Tract data.
Article in NeuroImage, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed.
- Computation and resource efficient genome-wide association analysis for large-scale imaging studies.Nature communications · 2026Article
- Computation and resource efficient genome-wide association analysis for large-scale imaging studies.medRxiv : the preprint server for health sciences · 2025Article
- Statistical Learning Methods for Neuroimaging Data Analysis with Applications.Annual review of biomedical data science · 2023Review
- Modeling multivariate age-related imaging variables with dependencies.Statistics in medicine · 2022Article
- DADP: Dynamic abnormality detection and progression for longitudinal knee magnetic resonance images from the Osteoarthritis Initiative.Medical image analysis · 2022Article
- Fast Univariate Inference for Longitudinal Functional Models.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2022Article
- Disentangling the effects of early caregiving experience and heritable factors on brain white matter development in rhesus monkeys.NeuroImage · 2019Article
- Functional Mixed-Effects Modeling of Longitudinal Duchenne Muscular Dystrophy Electrical Impedance Myography Data Using State-Space Approach.IEEE transactions on bio-medical engineering · 2019Article
- Spatially Adaptive Varying Correlation Analysis for Multimodal Neuroimaging Data.IEEE transactions on medical imaging · 2019Article
- FMEM: Functional Mixed Effects Models for Longitudinal Functional Responses.Statistica Sinica · 2019Article
- Proceedings of the 2017 annual meeting of the Fetal Alcohol Spectrum Disorders study group.Alcohol (Fayetteville, N.Y.) · 2018Article
- Dynamic prediction in functional concurrent regression with an application to child growth.Statistics in medicine · 2018Article
- Novel metrics for growth model selection.Emerging themes in epidemiology · 2018Article
- HFPRM: Hierarchical Functional Principal Regression Model for Diffusion Tensor Image Bundle Statistics.Information processing in medical imaging : proceedings of the ... conference · 2017Article
- Quantitative tract-based white matter heritability in twin neonates.NeuroImage · 2015Article
- Functional Nonlinear Mixed Effects Models for Longitudinal Image Data.Information processing in medical imaging : proceedings of the ... conference · 2015Article
- Functional-mixed effects models for candidate genetic mapping in imaging genetic studies.Genetic epidemiology · 2014Article
- Longitudinal High-Dimensional Principal Components Analysis with Application to Diffusion Tensor Imaging of Multiple Sclerosis.The annals of applied statisticsArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Many longitudinal imaging studies have collected repeated diffusion tensor magnetic resonance imaging data to understand white matter maturation and structural connectivity pattern in normal controls and diseased subjects. There is an urgent demand for the development of statistical methods for the analysis of diffusion properties along fiber tracts and clinical data obtained from longitudinal studies. Jointly analyzing repeated fiber-tract diffusion properties and covariates (e.g., age or gender) raises several major challenges including (i) infinite-dimensional functional response data, (ii) complex spatial-temporal correlation structure, and (iii) complex spatial smoothness. To address these challenges, this article is to develop a functional mixed effects modeling (FMEM) framework to delineate the dynamic changes of diffusion properties along major fiber tracts and their association with a set of covariates of interest and the structure of the variability of these white matter tract properties in various longitudinal studies. Our FMEM consists of a functional mixed effects model for addressing all three challenges, an efficient method for spatially smoothing varying coefficient functions, an estimation method for estimating the spatial-temporal correlation structure, a test procedure with local and global test statistics for testing hypotheses of interest associated with functional response, and a simultaneous confidence band for quantifying the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FMEM and to demonstrate that FMEM significantly outperforms the standard pointwise mixed effects modeling approach. We apply FMEM to study the spatial-temporal dynamics of white-matter fiber tracts in a clinical study of neurodevelopment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.