Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) . Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations
Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in ep...
In multilevel settings such as individual participant data meta-analysis, a variable is ‘systematica...
The goal ofmultiple imputation is to provide valid inferences for statistical estimates from incompl...
Multivariate Imputation by Chained Equations (MICE) is the name of software for imputing incomplete...
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 ...
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 ...
Multiple imputation by chained equations (MICE) is the most common method for imputing missing data....
Missing data are a common occurrence in real datasets. For epidemiological and prognostic factors st...
Multiple imputation is a practical, principled approach to handling missing data. When used to imput...
Multiple imputation by chained equations (MICE) has emerged as a popular approach for handling missi...
Abstract. Multiple imputation (MI) is a practical, principled approach to han-dling missing data. Wh...
Many variables that are analyzed by social scientists are nominal in nature. When missing data occur...
Following the seminal publications of Rubin about thirty years ago, statisticians have become increa...
Multiple imputation (MI) is used to handle missing at random (MAR) data. Despite warnings from stati...
The goal of multiple imputation is to provide valid inferences for statistical estimates from incomp...
Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in ep...
In multilevel settings such as individual participant data meta-analysis, a variable is ‘systematica...
The goal ofmultiple imputation is to provide valid inferences for statistical estimates from incompl...
Multivariate Imputation by Chained Equations (MICE) is the name of software for imputing incomplete...
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 ...
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 ...
Multiple imputation by chained equations (MICE) is the most common method for imputing missing data....
Missing data are a common occurrence in real datasets. For epidemiological and prognostic factors st...
Multiple imputation is a practical, principled approach to handling missing data. When used to imput...
Multiple imputation by chained equations (MICE) has emerged as a popular approach for handling missi...
Abstract. Multiple imputation (MI) is a practical, principled approach to han-dling missing data. Wh...
Many variables that are analyzed by social scientists are nominal in nature. When missing data occur...
Following the seminal publications of Rubin about thirty years ago, statisticians have become increa...
Multiple imputation (MI) is used to handle missing at random (MAR) data. Despite warnings from stati...
The goal of multiple imputation is to provide valid inferences for statistical estimates from incomp...
Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in ep...
In multilevel settings such as individual participant data meta-analysis, a variable is ‘systematica...
The goal ofmultiple imputation is to provide valid inferences for statistical estimates from incompl...