Multiple imputation of discrete and continuous data by fully conditional specification
S Van Buuren - Statistical methods in medical research, 2007 - journals.sagepub.com
The goal of multiple imputation is to provide valid inferences for statistical estimates from
incomplete data. To achieve that goal, imputed values should preserve the structure in the …
incomplete data. To achieve that goal, imputed values should preserve the structure in the …
Machine learning and integrative analysis of biomedical big data
Recent developments in high-throughput technologies have accelerated the accumulation
of massive amounts of omics data from multiple sources: genome, epigenome …
of massive amounts of omics data from multiple sources: genome, epigenome …
[BOOK][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 …
Multiple imputation using chained equations: issues and guidance for practice
Multiple imputation by chained equations is a flexible and practical approach to handling
missing data. We describe the principles of the method and show how to impute categorical …
missing data. We describe the principles of the method and show how to impute categorical …
[BOOK][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 …
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 …
mice: Multivariate imputation by chained equations in R
S Van Buuren, K Groothuis-Oudshoorn - Journal of statistical software, 2011 - jstatsoft.org
The R package mice imputes incomplete multivariate data by chained equations. The
software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R …
software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R …
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 …
[BOOK][B] Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis
FE Harrell - 2001 - Springer
Many texts are excellent sources of knowledge about individual statistical tools, but the art of
data analysis is about choosing and using multiple tools. Instead of presenting isolated …
data analysis is about choosing and using multiple tools. Instead of presenting isolated …
[BOOK][B] Applied logistic regression
A new edition of the definitive guide to logistic regression modeling for health science and
other applications This thoroughly expanded Third Edition provides an easily accessible …
other applications This thoroughly expanded Third Edition provides an easily accessible …