Results 301 to 310 of about 24,713,244 (334)

An Experimental Survey of Missing Data Imputation Algorithms

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

Missing Data Imputation: A Comprehensive Review

Journal of Computer and Communications
Majed M. Alwateer, E. Atlam, M. M. A. El-Raouf, Osama A. Ghoneim, Ibrahim Gad   +4 more
semanticscholar   +1 more source

Incremental Bayesian matrix/tensor learning for structural monitoring data imputation and response forecasting

, 2021
Pu Ren, Xinyu Chen, Lijun Sun, Hao Sun
semanticscholar   +1 more source

Missing response data: To impute or not a impute?

Controlled Clinical Trials, 1988
openaire   +1 more source

Imputation of Missing Network Data

2017
Huisman, Mark, Krause, Robert W.
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, Karel G M Moons   +1 more
exaly  

Multiple imputation using chained equations: Issues and guidance for practice

Statistics in Medicine, 2011
Ian R White, Patrick Royston, Angela M Wood   +2 more
exaly  

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

Journal of Clinical Epidemiology, 2019
Paul Madley-Dowd, Rachael A Hughes, Kate Tilling   +2 more
exaly  

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

American Journal of Epidemiology, 2010
Katherine J Lee, John B Carlin
exaly