Work

Reducing the complexity of high-dimensional environmental data: An analytical framework using LASSO with considerations of confounding for statistical inference

Year: 2023

Type: article

Study design: Observational Study

Source: International Journal of Hygiene and Environmental Health

DOI: 10.1016/j.ijheh.2023.114116

Authors: Seth Frndak, Guan Yu, Youssef Oulhote, Elena I. Queirolo, Gabriel Barg, Marie Vahter, Nelly Mañay, Fabiana Peregalli, James R. Olson, Zia Ahmed, Katarzyna Kordas

Institutions: State University of New York, University at Buffalo, State University of New York, University of Pittsburgh, University of Massachusetts Amherst, Universidad Católica del Uruguay, Karolinska Institutet, Universidad de la República de Uruguay

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: State University of New York, University at Buffalo, National Institute of Environmental Health Sciences

Awards: Low-level Exposure to Multiple Metals: Effects on Cognition and Behavior, Is Low-Level Arsenic Exposure Related to Neurobehavioral Deficits in Children, Nutritional and Heavy Metals: Effects on Child Learning and Behavior in Uruguay

OpenAlex ID: W4321324676

FWCI: 2.435

Cites: 48

Cited by: 12

Related to: 10