A survey on missing data in machine learning

T Emmanuel, T Maupong, D Mpoeleng, T Semong… - Journal of Big …, 2021 - Springer
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 …

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 …

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 …

[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 …

A comparison of multiple imputation methods for missing data in longitudinal studies

MH Huque, JB Carlin, JA Simpson, KJ Lee - BMC medical research …, 2018 - Springer
Background Multiple imputation (MI) is now widely used to handle missing data in
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 …

[图书][B] Multiple imputation and its application

JR Carpenter, JW Bartlett, TP Morris, AM Wood… - 2023 - books.google.com
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 …

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 …

[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 …

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 …