We propose a model-based clustering method for high-dimensional longitudinal data via regularization in this paper. This study was motivated by the Trial of Activity in Adolescent Girls (TAAG), which aimed to examine multilevel factors related to the change of physical activity by following up a cohort of 783 girls over 10 years from adolescence to early adulthood. Our goal is to identify the intrinsic grouping of subjects with similar patterns of physical activity trajectories and the most relevant predictors within each group. The previous analyses conducted clustering and variable selection in two steps, while our new method can perform the tasks simultaneously. Within each cluster, a linear mixed-effects model (LMM) is fitted with a doubly penalized likelihood to induce sparsity for parameter estimation and effect selection. The large-sample joint properties are established, allowing the dimensions of both fixed and random effects to increase at an exponential rate of the sample size, with a general class of penalty functions. Assuming subjects are drawn from a Gaussian mixture distribution, model effects and cluster labels are estimated via a coordinate descent algorithm nested inside the Expectation-Maximization (EM) algorithm. Bayesian Information Criterion (BIC) is used to determine the optimal number of clusters and the values of tuning parameters. Our numerical studies show that the new method has satisfactory performance and is able to accommodate complex data with multilevel and/or longitudinal effects.
- Award ID(s):
- 1934962
- NSF-PAR ID:
- 10352988
- Editor(s):
- Harezlak, Jaroslaw
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 17
- Issue:
- 5
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0268376
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Methods PA was measured in 40 participants ranging in age from 14 to 78 years using ActiGraph wrist‐worn accelerometers. Wear time spanned 24–77 hours, with a modal wear time of 50 hours.
Results We show that the Pokot spend large amounts of time in moderate‐to‐vigorous physical activity (MVPA), achieving an average of 99.14 ± 7.25 minutes per day in MVPA. Males and younger participants tended to spend more time in MVPA. However, older participants were still physically active and engaged in over 50 minutes per day of MVPA.
Conclusions The Pokot are highly physically active from adolescence through adulthood. Other pastoralist groups may display a similar pattern of PA. During human evolution, lifespans increased, and lifestyles were characterized by a relatively high level of physical activity. The human aging process may be adapted for activity throughout life, and lifelong activity may have played an important role in increases in human longevity during evolution.
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Methods Data from the first wave of the EveryBODY study, a large sample of Australian adolescents aged 11–19 years (
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Conclusions Romantic experience emerged as a novel correlate for adolescents' eating pathology. Future research should uncover the contextual factors within relationships that may contribute to this association.
Public Significance The initiation of romantic relationships is normative during adolescence. However, adolescents' romantic desirability is often determined by their physical appearance, increasing the risk for eating pathology. Among a large sample of Australian adolescents, romantic involvement was associated with greater likelihood of clinical threshold eating pathology for adolescent boys and girls, regardless of sexual attraction. It is urgent to identify the factors within romantic relationships that are associated with eating pathology.
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0268376
