Construction and assessment of prediction rules for binary outcome in the presence of missing predictor data using multiple imputation and cross-validation: Methodological approach and data-based evaluation.

Mertens, Bart J A; Banzato, Erika; de Wreede, Liesbeth C

Mertens, Bart J A; Banzato, Erika; de Wreede, Liesbeth C.

Afiliación

Mertens BJA; Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Banzato E; Department of Statistical Sciences, University of Padova, Padova, Italy.
de Wreede LC; Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.

Biom J ; 62(3): 724-741, 2020 05.

Article en En | MEDLINE | ID: mdl-32052492

Asunto(s)

Biometría/métodos; Análisis de Varianza; Calibración

Palabras clave

binary outcome; calibration; cross-validation; multiple imputation; prediction

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Biometría Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Biom J Año: 2020 Tipo del documento: Article País de afiliación: Países Bajos

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