Results 181 to 190 of about 204,036 (213)
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[Imputation of missing data].

Nederlands tijdschrift voor geneeskunde, 2013
In medical research missing data are sometimes inevitable. Different missingness mechanisms can be distinguished: (a) missing completely at random; (b) missing by design; (c) missing at random, and (d) missing not at random. If participants with missing data are excluded from statistical analyses, this can lead to biased study results and loss of ...
Ralph C A, Rippe   +2 more
openaire   +1 more source

An Experimental Survey of Missing Data Imputation Algorithms

IEEE Transactions on Knowledge and Data Engineering, 2022
Xiaoye Miao, Yangyang Wu, Lu Chen
exaly  

Multiple imputation with missing data indicators

Statistical Methods in Medical Research, 2021
Lauren J Beesley   +2 more
exaly  

Imputation of the Missing Data

2013
We may consider the existence of missing observations as unimportant, considering that the risk of misunderstanding is negligible. The surveyor assumes some model that allows adequately explaining the variable of interest. In such cases, we are able to predict the unknown values and to plug them into some estimator.
openaire   +1 more source

Review: A gentle introduction to imputation of missing values

Journal of Clinical Epidemiology, 2006
Geert J M G van der Heijden   +1 more
exaly  

Multiple imputation using chained equations: Issues and guidance for practice

Statistics in Medicine, 2011
Ian R White   +2 more
exaly  

Imputation of Missing Network Data

2017
Huisman, Mark, Krause, Robert W.
openaire   +1 more source

The proportion of missing data should not be used to guide decisions on multiple imputation

Journal of Clinical Epidemiology, 2019
Paul Madley-Dowd   +2 more
exaly  

Multiple Imputation for Missing Data: Fully Conditional Specification Versus Multivariate Normal Imputation

American Journal of Epidemiology, 2010
Katherine J Lee   +2 more
exaly  

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