MICE for multiple imputation of missing values
The publication of Royston (2004)'s Stata implementation of the MICE method for multiple imputation of missing values has stimulated much interest, comment and further development of the software. In this talk I will describe enhancements of what used to be called mvis.ado and is now known as mice.ado. The main changes are greatly increased flexibility in the specification of the prediction equations for individual variables, better handling of ordered and nominal categoric variables, and support for so-called passive imputation in which derived variables are updated from primary variables. All of these features reflect van Buuren's implementation of MICE on a different statistical platform. I will demonstrate their use by an example with real data. An article on the topic is in preparation (Royston 2005).
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