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UID:20250918T165000EDT-9405jrUVFN@132.216.98.100
DTSTAMP:20250918T205000Z
DESCRIPTION:Title: Bayesian nonparametric solutions to analyze nutritional 
 Survey Data.\n\nAbstract: Website: https://www.hsph.harvard.edu/briana-ste
 phenson/\n\n\nDietary intake is a major modifiable risk factor for cardiov
 ascular disease that has a disproportionate impact on low-income and racia
 l/ethnic minorities. Population-based studies provide researchers with a s
 napshot of dietary habits of a target population through the collection of
  dietary intake assessments (food frequency questionnaire\, 24-hour dietar
 y recalls) from a large sample of participants. Through the implementation
  of complex survey designs and recruitment strategies\, researchers can ob
 tain a diverse random sample of a target population to better understand t
 he larger target population of interest. Characterization of dietary intak
 e from these assessment tools can often be quite complex due to the high-d
 imensional structure of the data. When analyzing national multistage surve
 y data with unequal probabilities of selection and response inherent in th
 e design\, an additional layer of complexity is presented.\n	\n	Bayesian non
 parametrics offers a more efficient solution that can accommodate (1) comp
 lex high dimensionality of dietary intake data\, (2) volume of a large pop
 ulation size\, (3) preserve model stability in the presence of sparsely co
 nsumed foods\, and (4) integrate prior information with observed data. Usi
 ng diet consumption data collected in large population-based survey cohort
 s\, this talk will discuss flexible solutions Bayesian nonparametric model
 -based clustering techniques can provide to manage the complexities of die
 tary heterogeneity present in populations typically understudied and margi
 nalized (e.g. low-income or racial/ethnic minority) in the United States.
 \n\nPlease visit our website for the Zoom Link: /epi-
 biostat-occh/seminars-events/seminars/biostati...\n\n \n\n \n
DTSTART:20221109T203000Z
DTEND:20221109T213000Z
SUMMARY:Briana Joy K. Stephenson\, PhD\, Harvard T.H. Chan School of Public
  Health
URL:/mathstat/channels/event/briana-joy-k-stephenson-p
 hd-harvard-th-chan-school-public-health-343176
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