Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation

Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation

Abstract Background Missing values are a frequent issue in human studies. In many situations, multiple imputation (MI) is an appropriate missing data handling strategy, whereby missing values are imputed multiple times, the analysis is performed in every imputed data set, and the obtained estimates...

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Bibliographic Details
Main Authors: Simone Wahl, Anne-Laure Boulesteix, Astrid Zierer, Barbara Thorand, Mark A. van de Wiel
Format: Article
Language:English
Published: BMC 2016-10-01
Series:BMC Medical Research Methodology
Subjects:
Missing values
Incomplete data
Prediction model
Predictive performance
Bootstrap
Internal validation
Online Access:http://link.springer.com/article/10.1186/s12874-016-0239-7

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http://link.springer.com/article/10.1186/s12874-016-0239-7

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