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Wiley Interdisciplinary Reviews: Computational Statistics, ISSN 1939-5108, 01/2013, Volume 5, Issue 1, pp. 20 - 29
Missing data are a common problem in statistics. Imputation, or filling in the missing values, is an intuitive and flexible way to address the resulting... 
MCAR | imputation | MNAR | monotone missingness | MCMC | multiple imputation | MAR | Imputation | Monotone missingness | Multiple imputation | Datasets | Software | Data analysis | Filtration | Statistical analysis | Methodology | Data processing | Statistical methods | Data | Data smoothing | Statistics | Data reduction | Computer programs | Missing data | Data sets | Analysis | Graphical methods | Sampling methods | Handling | Strategy | Wire
Journal Article
2012, Chapman & Hall/CRC interdisciplinary statistics series, ISBN 9781439868249, xxv, 316
"Preface We are surrounded by missing data. Problems created by missing data in statistical analysis have long been swept under the carpet. These times are now... 
Missing observations (Statistics) | Multivariate analysis | Multiple imputation (Statistics)
Book
2012, 1. Aufl., Statistics in practice, ISBN 0470740523, 357
A practical guide to analysing partially observed data.Collecting, analysing and drawing inferences from data is central to research in the medical and social... 
Biomedical Research - methods | Medicine | Medical statistics
eBook
Journal of Statistical Software, ISSN 1548-7660, 2011, Volume 45, Issue 6, pp. 1 - 25
Multiple imputation provides a useful strategy for dealing with data sets that have missing values. Instead of filling in a single value for each missing... 
Monotone missing pattern | Multiple imputation | Markov chain Monte Carlo | Markow chain Monte Carlo | multiple imputation | STATISTICS & PROBABILITY | monotone missing pattern | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | Markov chain | Monte Carlo
Journal Article
American Journal of Epidemiology, ISSN 0002-9262, 08/2010, Volume 172, Issue 4, pp. 478 - 487
Journal Article
International Statistical Review, ISSN 0306-7734, 05/2019, Volume 87, Issue S1, pp. S192 - S218
Journal Article
Journal of Statistical Software, ISSN 1548-7660, 2011, Volume 45, Issue 4, pp. 1 - 20
Missing data are a common occurrence in real datasets. For epidemiological and prognostic factors studies in medicine, multiple imputation is becoming the... 
Missing data | Continuous variables | Categorical variables | Multiple imputation | Chained equations | continuous variables | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MISSING VALUES | EMPHASIS | multiple imputation | STATISTICS & PROBABILITY | UPDATE | ICE | chained equations | categorical variables | missing data
Journal Article
Journal of Statistical Software, ISSN 1548-7660, 2016, Volume 74, Issue 7, pp. 1 - 16
The package VIM (Templ, Alfons, Kowarik, and Prantner 2016) is developed to explore and analyze the structure of missing values in data using visualization... 
Imputation methods | Missing values | imputation methods | MISSING DATA | STATISTICS & PROBABILITY | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MULTIPLE IMPUTATION | missing values
Journal Article
Journal of Statistical Software, ISSN 1548-7660, 2011, Volume 45, Issue 2, pp. 1 - 31
Our mi package in R has several features that allow the user to get inside the imputation process and evaluate the reasonableness of the resulting models and... 
Model diagnostics | Multiple imputation | Weakly informative prior | Chained equations | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | REGRESSION-MODELS | model diagnostics | multiple imputation | STATISTICS & PROBABILITY | chained equations | weakly informative prior
Journal Article
1987, Wiley series in probability and mathematical statistics. Applied probability and statistics, ISBN 9780471087052, xxix, 258 p. --
Book
Journal Article