ArticleJournal of the American Statistical Association2018
Variable Selection for Skewed Model-Based Clustering: Application to the Identification of Novel Sleep Phenotypes.
Article in Journal of the American Statistical Association, 2018. 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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Who cites it
18 citing papers in PubMed.
- Article
- Sleep fragmentation and heightened inflammation: A latent profile subtype predicting nine-year major depressive disorder severity in the MIDUS study.Brain, behavior, & immunity - health · 2026Article
- Pediatric precision sleep network: a study protocol for identifying sleep signatures of mental health risk in peri-adolescents.BMC pediatrics · 2026Article
- A New Method to Interpret Cluster Analysis Results in the Presence of Heterogeneous Clusters.Journal for person-oriented research · 2026Article
- Article
- Sleep health profiles across six population-based cohorts and recommendations for validating clustering models.Sleep health · 2025Article
- Article
- Designing work for healthy sleep: A multidimensional, latent transition approach to employee sleep health.Journal of occupational health psychology · 2024Article
- Ten-Year Stability of an Insomnia Sleeper Phenotype and Its Association With Chronic Conditions.Psychosomatic medicine · 2024Article
- Hard Work Makes It Hard to Sleep: Work Characteristics Link to Multidimensional Sleep Health Phenotypes.Journal of business and psychology · 2024Article
- Article
- Neurobehavioral Reward and Sleep-Circadian Profiles Predict Present and Next-Year Mania/Hypomania Symptoms.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2023Article
- Article
- Quantifying Distances Between Non-Elliptical Clusters to Enhance the Identification of Meaningful Emotional Reactivity Subtypes.Data science in science · 2022Article
- Multidimensional sleep health in a diverse, aging adult cohort: Concepts, advances, and implications for research and intervention.Sleep health · 2021Article
- Beyond single sleep measures: A composite measure of sleep health and its associations with psychological and physical well-being in adulthood.Social science & medicine (1982) · 2021Article
- Estimating Heterogeneous Effects of a Policy Intervention across Organizations when Organization Affiliation is Missing for the Control Group: Application to the Evaluation of Accountable Care Organizations.Health services & outcomes research methodology · 2021Article
- Multidimensional sleep health domains in older men and women: an actigraphy factor analysis.Sleep · 2021Article
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Authors and funding
5 authors.
Funding
Abstract
In sleep research, applying finite mixture models to sleep characteristics captured 8 through multiple data types, including self-reported sleep diary, a wrist monitor capturing movement (actigraphy), and brain waves (polysomnography), may suggest new phenotypes that reflect underlying disease mechanisms. However, a direct mixture model application is challenging because there are many sleep variables from which to choose, and sleep variables are often highly skewed even in homogenous samples. Moreover, previous sleep research findings indicate that some of the most clinically interesting solutions will be those that incorporate all three data types. Thus, we present two novel skewed variable selection algorithms based on the multivariate skew normal (MSN) distribution: one that selects the best set of variables ignoring data type and another that embraces the exploratory nature of clustering and suggests multiple statistically plausible sets of variables that each incorporate all data types. Through a simulation study we empirically compare our approach with other asymmetric and normal dimension reduction strategies for clustering. Finally, we demonstrate our methods using a sample of older adults with and without insomnia. The proposed MSN-based variable selection algorithm appears to be suitable for both MSN and multivariate normal cluster distributions, especially with moderate to large sample sizes.
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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.