Comparative efficacy of three Bayesian variable selection methods in the context of weight loss in obese women.

Pesenti, Nicola; Quatto, Piero; Colicino, Elena; Cancello, Raffaella; Scacchi, Massimo; Zambon, Antonella

Pesenti, Nicola; Quatto, Piero; Colicino, Elena; Cancello, Raffaella; Scacchi, Massimo; Zambon, Antonella.

Afiliación

Pesenti N; Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, University of Milano-Bicocca, Milan, Italy.
Quatto P; Department of Economics, Management and Statistics, University of Milano-Bicocca, Milan, Italy.
Colicino E; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Cancello R; Obesity Unit and Laboratory of Nutrition and Obesity Research, Department of Endocrine and Metabolic Diseases, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Scacchi M; Division of Endocrinology and Metabolic Diseases, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Zambon A; Department of Clinical Science and Community Health, University of Milan, Milan, Italy.

Front Nutr ; 10: 1203925, 2023.

Article en En | MEDLINE | ID: mdl-37533570

Palabras clave

Bayesian kernel machine regression; Bayesian least absolute shrinkage and selection operator; Bayesian semiparametric regression; correlated exposures; obesity; variable selection

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Front Nutr Año: 2023 Tipo del documento: Article País de afiliación: Italia

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