Using multiple imputation to address the inconsistent distribution of a controlling variable when modeling an infrequent outcome.

Zhang, Yujia; Crawford, Sara; Boulet, Sheree L; Monsour, Michael; Cohen, Bruce; McKane, Patricia; Freeman, Karen

Zhang, Yujia; Crawford, Sara; Boulet, Sheree L; Monsour, Michael; Cohen, Bruce; McKane, Patricia; Freeman, Karen.

Afiliación

Zhang Y; Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA.
Crawford S; Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA.
Boulet SL; Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA.
Monsour M; Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA.
Cohen B; Massachusetts Department of Public Health, Boston.
McKane P; Michigan Department of Community Health, Lansing.
Freeman K; Florida Department of Health, Tallahassee.

J Mod Appl Stat Methods ; 16(1): 744-752, 2017.

Article en En | MEDLINE | ID: mdl-30393468

Palabras clave

assisted reproductive technology; inconsistent data distribution; multiple imputation; weighted sequential hot deck

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Mod Appl Stat Methods Año: 2017 Tipo del documento: Article País de afiliación: Gabón

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