Matching and Weighting Multiply Imputed Datasets
Checks for the mimira Class
Checks for the wimids Class
Matches Multiply Imputed Datasets
Matched Multiply Imputed Datasets
Multiply Imputed Pooled Outcome
Multiply Imputed Repeated Analyses
Pools Estimates by Rubin's Rules
Create a mimids object
Create a wimids object
Combine mimids and wimids Objects by Columns
Extracts Multiply Imputed Datasets
Checks for the mimids Class
Checks for the mimipo Class
Trim Weights
Weights Multiply Imputed Datasets
Weighted Multiply Imputed Datasets
Evaluates an Expression in Matched or Weighted Multiply Imputed Datase...
Provides essential tools for the pre-processing techniques of matching and weighting multiply imputed datasets. The package includes functions for matching within and across multiply imputed datasets using various methods, estimating weights for units in the imputed datasets using multiple weighting methods, calculating causal effect estimates in each matched or weighted dataset using parametric or non-parametric statistical models, and pooling the resulting estimates according to Rubin's rules (please see <https://journal.r-project.org/archive/2021/RJ-2021-073/> for more details).
Useful links