Association between dietary polyphenols intake and an oxidative stress biomarker: interest of multiple imputation for handling missing covariates and outcomes
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2055-0928
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Association between dietary polyphenols intake and an oxidative stress biomarker: interest of multiple imputation for handling missing covariates and outcomes ; volume:2 ; number:1 ; day:28 ; month:11 ; year:2016 ; pages:1-10 ; date:12.2016
BMC nutrition ; 2, Heft 1 (28.11.2016), 1-10, 12.2016
- Creator
-
Montlahuc, Claire
- Contributor
-
Julia, Chantal
Touvier, Mathilde
Fézeu, Léopold
Hercberg, Serge
Galan, Pilar
Kesse-Guyot, Emmanuelle
Chevret, Sylvie
SpringerLink (Online service)
- DOI
-
10.1186/s40795-016-0114-2
- URN
-
urn:nbn:de:1111-201701141124
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:52 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Montlahuc, Claire
- Julia, Chantal
- Touvier, Mathilde
- Fézeu, Léopold
- Hercberg, Serge
- Galan, Pilar
- Kesse-Guyot, Emmanuelle
- Chevret, Sylvie
- SpringerLink (Online service)
Other Objects (12)
Simulation study - handling missing covariates in the context of external validation
Comparison of imputation methods for handling missing categorical data with univariate pattern
Multiple imputation for handling missing outcome data when estimating the relative risk
Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study
Mechanism-aware imputation: a two-step approach in handling missing values in metabolomics
Nonparametric regression with selectively missing covariates
Missing Data, Imputation, and Endogeneity
Efficient probit estimation with partially missing covariates
Efficient probit estimation with partially missing covariates
Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework
Missing value imputation for epistatic MAPs
Simulation study - handling missing covariates in the context of external validation
Comparison of imputation methods for handling missing categorical data with univariate pattern
Multiple imputation for handling missing outcome data when estimating the relative risk
Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study
Mechanism-aware imputation: a two-step approach in handling missing values in metabolomics
Nonparametric regression with selectively missing covariates
Missing Data, Imputation, and Endogeneity
Efficient probit estimation with partially missing covariates
Efficient probit estimation with partially missing covariates
Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework
Missing value imputation for epistatic MAPs
Simulation study - handling missing covariates in the context of external validation
Comparison of imputation methods for handling missing categorical data with univariate pattern
Multiple imputation for handling missing outcome data when estimating the relative risk
Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study
Mechanism-aware imputation: a two-step approach in handling missing values in metabolomics
Nonparametric regression with selectively missing covariates
Missing Data, Imputation, and Endogeneity
Efficient probit estimation with partially missing covariates
Efficient probit estimation with partially missing covariates
Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework