His work with them showed how effective multiple imputation could be. The organizations also created imputed data that others could then use in their own analyses. By the 1990s, computer memory and ...

linear regression — cannot function if data values are missing. To mitigate this problem, imputation techniques replace missing data with values consistent with the observed patterns.

This course aims to provide a theoretical and practical introduction to multiple imputation methods for dealing with missing data in straightforward situations ... and question and answer sessions, ...

Multiple imputation is a principled approach to account for missing data in analyses where valid results depends ... live summary plus question & answer sessions, and live computer practical exercises ...

In this paper we propose a new imputation method satisfying edits. Imputation is a frequently used way to treat missing data due to item-nonresponse in surveys. In some cases, especially at national ...

Next, we will briefly cover early methods for handling missing data, such as complete case analysis and single imputation techniques (mean, hot deck, etc.), and why in practice they can produce ...