Multiple Imputation by Chained Equations with Multilevel Data
Suggestion of conditional imputation models to use accordingly to the ...
Imputation by a two-level logistic model based on a two-stage estimato...
Imputation based on Heckman model for multilevel data.
Imputation by a two-level heteroscedastic normal model based on a two-...
Predictive mean matching imputation for two-level variable
Imputation by a two-level Poisson model based on a two-stage estimator
Imputation of univariate missing data using a Bayesian logistic mixed ...
Imputation of univariate missing data using a Bayesian linear mixed mo...
Imputation of count variable using a Bayesian mixed model based on non...
Imputation of univariate missing data by a Bayesian multivariate gener...
Parallel calculations for Multivariate Imputation by Chained Equations
Multiple Imputation by Chained Equations with Multilevel Data
Overimputation diagnostic plot
Graphical investigation for the number of generated datasets
Addons for the 'mice' package to perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated to sporadically and systematically missing values. Imputation of continuous, binary or count variables are available. Following the recommendations of Audigier, V. et al (2018) <doi:10.1214/18-STS646>, the choice of the imputation method for each variable can be facilitated by a default choice tuned according to the structure of the incomplete dataset. Allows parallel calculation and overimputation for 'mice'.