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Missing data

Known as: MCAR, Missingness, Missing at random 
In statistics, missing data, or missing values, occur when no data value is stored for the variable in an observation. Missing data are a common… Expand
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Papers overview

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Review
2017
Review
2017
In medical imaging, Computer Aided Diagnosis (CAD) is a rapidly growing dynamic area of research. In recent years, significant… Expand
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Highly Cited
2016
Highly Cited
2016
Thank you for downloading applied missing data analysis. Maybe you have knowledge that, people have look hundreds times for their… Expand
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Highly Cited
2011
Highly Cited
2011
Amelia II is a complete R package for multiple imputation of missing data. The package implements a new expectation-maximization… Expand
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Highly Cited
2007
Highly Cited
2007
Part 1. A Gentle Introduction to Missing Data. The Concept of Missing Data. The Prevalence of Missing Data. Why Data Might Be… Expand
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Highly Cited
2007
Highly Cited
2007
Memory-based collaborative filtering algorithms have been widely adopted in many popular recommender systems, although these… Expand
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Highly Cited
2004
Highly Cited
2004
Following the seminal publications of Rubin about thirty years ago, statisticians have become increasingly aware of the… Expand
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Highly Cited
2003
Highly Cited
2003
 
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Highly Cited
2001
Highly Cited
2001
A Monte Carlo simulation examined the performance of 4 missing data methods in structural equation models: full information… Expand
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Highly Cited
2001
Highly Cited
2001
Abstract Human speech perception is robust in the face of a wide variety of distortions, both experimentally applied and… Expand
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Highly Cited
1994
Highly Cited
1994
Abstract For missing data problems, Tanner and Wong have described a data augmentation procedure that approximates the actual… Expand
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