Results 241 to 250 of about 175,631 (262)

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

Journal of Clinical Epidemiology, 2019
Jon Heron, Kate Tilling, Rachael Hughes
exaly  

Multiple imputation for missing data: fully conditional specification versus multivariate normal imputation.

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

Using the outcome for imputation of missing predictor values was preferred

Journal of Clinical Epidemiology, 2006
Theo Stijnen, Frank E. Harrell, Jr., Karel G. M. Moons   +2 more
exaly  

Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: A clinical example

Journal of Clinical Epidemiology, 2006
Theo Stijnen, Karel G. M. Moons
exaly  

Missing Data, Imputation of

2022
openaire   +1 more source

A class center based approach for missing value imputation

Knowledge-Based Systems, 2018
Chih-Fong Tsai
exaly  

Impact of imputation of missing values on classification error for discrete data

Pattern Recognition, 2008
Lukasz Kurgan, Jennifer Dy, Alireza Farhangfar   +2 more
exaly  

Multiple imputation of missing values was not necessary before performing a longitudinal mixed-model analysis

Journal of Clinical Epidemiology, 2013
Wieke de Vente, Martijn W Heymans
exaly  

Missing Data Imputation

2011
openaire   +1 more source

Handling missing values: A study of popular imputation packages in R

Knowledge-Based Systems, 2018
Madan Lal Yadav, Basav Roychoudhury
exaly