Sparse group variable selection for gene-environment interactions in the longitudinal study.

Zhou, Fei; Lu, Xi; Ren, Jie; Fan, Kun; Ma, Shuangge; Wu, Cen

Zhou, Fei; Lu, Xi; Ren, Jie; Fan, Kun; Ma, Shuangge; Wu, Cen.

Afiliación

Zhou F; Department of Statistics, Kansas State University, Manhattan, Kansas, 66506, USA.
Lu X; Department of Statistics, Kansas State University, Manhattan, Kansas, 66506, USA.
Ren J; Department of Biostatistics and Health Data Sciences, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA.
Fan K; Department of Statistics, Kansas State University, Manhattan, Kansas, 66506, USA.
Ma S; Department of Biostatistics, Yale University, New Haven, Connecticut, 06520, USA.
Wu C; Department of Statistics, Kansas State University, Manhattan, Kansas, 66506, USA.

Genet Epidemiol ; 46(5-6): 317-340, 2022 07.

Article en En | MEDLINE | ID: mdl-35766061

Asunto(s)

Asma; Interacción Gen-Ambiente; Asma/genética; Simulación por Computador; Humanos; Estudios Longitudinales; Modelos Genéticos

Palabras clave

gene-environment interaction; longitudinal data; penalization; quadratic inference function; sparse group selection

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Asma / Interacción Gen-Ambiente Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Genet Epidemiol Asunto de la revista: EPIDEMIOLOGIA / GENETICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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