A survey on missing data in machine learning
Abstract Machine learning has been the corner stone in analysing and extracting information
from data and often a problem of missing values is encountered. Missing values occur …
from data and often a problem of missing values is encountered. Missing values occur …
Missing data: An update on the state of the art.
CK Enders - Psychological Methods, 2023 - psycnet.apa.org
The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled
“Missing data: Our view of the state of the art,” currently the most highly cited paper in the …
“Missing data: Our view of the state of the art,” currently the most highly cited paper in the …
Principled missing data methods for researchers
Y Dong, CYJ Peng - SpringerPlus, 2013 - Springer
The impact of missing data on quantitative research can be serious, leading to biased
estimates of parameters, loss of information, decreased statistical power, increased standard …
estimates of parameters, loss of information, decreased statistical power, increased standard …
[图书][B] Flexible imputation of missing data
S Van Buuren - 2018 - books.google.com
Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or
mean imputation, only work under highly restrictive conditions, which are often not met in …
mean imputation, only work under highly restrictive conditions, which are often not met in …
A comparison of multiple imputation methods for missing data in longitudinal studies
Background Multiple imputation (MI) is now widely used to handle missing data in
longitudinal studies. Several MI techniques have been proposed to impute incomplete …
longitudinal studies. Several MI techniques have been proposed to impute incomplete …
Multiple imputation as a flexible tool for missing data handling in clinical research
CK Enders - Behaviour research and therapy, 2017 - Elsevier
The last 20 years has seen an uptick in research on missing data problems, and most
software applications now implement one or more sophisticated missing data handling …
software applications now implement one or more sophisticated missing data handling …
[图书][B] Multiple imputation and its application
Multiple Imputation and its Application The most up-to-date edition of a bestselling guide to
analyzing partially observed data In this comprehensively revised Second Edition of Multiple …
analyzing partially observed data In this comprehensively revised Second Edition of Multiple …
Forced displacement from rental housing: Prevalence and neighborhood consequences
M Desmond, T Shollenberger - Demography, 2015 - Springer
Drawing on novel survey data of Milwaukee renters, this study documents the prevalence of
involuntary displacement from housing and estimates its consequences for neighborhood …
involuntary displacement from housing and estimates its consequences for neighborhood …
[图书][B] Applied missing data analysis
CK Enders - 2022 - books.google.com
The most user-friendly and authoritative resource on missing data has been completely
revised to make room for the latest developments that make handling missing data more …
revised to make room for the latest developments that make handling missing data more …
Missing data
PD Allison - The SAGE handbook of quantitative methods in …, 2009 - torrossa.com
Missing data are ubiquitous in psychological research. By missing data, I mean data that are
missing for some (but not all) variables and for some (but not all) cases. If data are missing …
missing for some (but not all) variables and for some (but not all) cases. If data are missing …