Benchmarking and Assessment for Multiple Imputation

The increased popularity of multiple imputation to obtain valid inference on incomplete data has identified two potential problems. First, imputation techniques are developed to solve distinct problems. They are evaluated on their performance on these problems, but are potentially of great scientific use outside of their target application. Such innovative applications remain unknown. Second, the target audience for multiple imputation consists of applied researchers from all scientific domains. These researchers often lack the statistical knowledge to understand the methodology behind these imputation techniques. How can these researchers decide what imputation technique would be suitable for their problem?

Integrating benchmarking into multiple imputation methodology can solve these problems. When it is possible to compare benchmarked techniques to one another, we can determine what would be the most suitable imputation method for specific data problems. This allows applied researchers to get the optimal imputation technology for their data, without the advanced statistical knowledge that is normally required when implementing multiple imputation techniques.