The impact of correlated exposures and missing data on multiple informant models used to identify critical exposure windows.

Bather, Jemar R; Horton, Nicholas J; Coull, Brent A; Williams, Paige L

Bather, Jemar R; Horton, Nicholas J; Coull, Brent A; Williams, Paige L.

Afiliação

Bather JR; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Horton NJ; Department of Mathematics and Statistics, Amherst College, Amherst, Massachusetts, USA.
Coull BA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Williams PL; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

Stat Med ; 42(8): 1171-1187, 2023 04 15.

Article em En | MEDLINE | ID: mdl-36647625

Assuntos

Modelos Estatísticos; Lactente; Humanos; Gravidez; Feminino; Probabilidade; Viés; Trimestres da Gravidez; Tamanho da Amostra

Palavras-chave

critical windows; exposure timing; generalized estimating equations; inverse probability weights; missing data; multiple informants

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estatísticos Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

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