ArticlePloS one2018
Functional principal component analysis for identifying multivariate patterns and archetypes of growth, and their association with long-term cognitive development.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Head circumference and intelligence, schooling, employment, and income: a systematic review.BMC pediatrics · 2024Pooled it
- Forecasting the Regional Demand for Medical Workers in Kazakhstan: The Functional Principal Component Analysis Approach.International journal of environmental research and public health · 2025Article
- Article
- Predicting health outcomes with intensive longitudinal data collected by mobile health devices: a functional principal component regression approach.BMC medical research methodology · 2024Article
- Latent deformation models for multivariate functional data and time-warping separability.Biometrics · 2023Article
- A Causal Mediation Model for Longitudinal Mediators and Survival Outcomes with an Application to Animal Behavior.Journal of agricultural, biological, and environmental statistics · 2023Article
- Human milk oligosaccharide composition and associations with growth: results from an observational study in the US.Frontiers in nutrition · 2023Article
- Functional principal component analysis for identifying the child growth pattern using longitudinal birth cohort data.BMC medical research methodology · 2022Article
- Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes.Journal of biomedical informatics · 2021Review
- CAUSAL MEDIATION ANALYSIS FOR SPARSE AND IRREGULAR LONGITUDINAL DATA.The annals of applied statistics · 2021Article
- Time dynamics of COVID-19.Scientific reports · 2020Article
- Dynamic prediction of time to a clinical event with sparse and irregularly measured longitudinal biomarkers.Biometrical journal. Biometrische Zeitschrift · 2020Article
- Identification of nutritionally modifiable hormonal and epigenetic drivers of positive and negative growth deviance in rural African fetuses and infants: Project protocol and cohort description.Gates open research · 2020Article
- Introducing a drift and diffusion framework for childhood growth research.Gates open research · 2020Article
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Authors and funding
7 authors.
Funding
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Abstract
For longitudinal studies with multivariate observations, we propose statistical methods to identify clusters of archetypal subjects by using techniques from functional data analysis and to relate longitudinal patterns to outcomes. We demonstrate how this approach can be applied to examine associations between multiple time-varying exposures and subsequent health outcomes, where the former are recorded sparsely and irregularly in time, with emphasis on the utility of multiple longitudinal observations in the framework of dimension reduction techniques. In applications to children's growth data, we investigate archetypes of infant growth patterns and identify subgroups that are related to cognitive development in childhood. Specifically, "Stunting" and "Faltering" time-dynamic patterns of head circumference, body length and weight in the first 12 months are associated with lower levels of long-term cognitive development in comparison to "Generally Large" and "Catch-up" growth. Our findings provide evidence for the statistical association between multivariate growth patterns in infancy and long-term cognitive development.
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