MITOOLS: Stata module of tools for analyzing multiple imputed datasets

The method of multiple imputation (MI) is used increasingly for analyzing datasets with missing observations. Two sets of tasks are required in order to implement the method: (a) generating multiple complete datasets in which missing values have been imputed by simulating from an appropriate probability distribution and (b) analyzing the multiple imputed datasets and combining complete data inferences from them to form an overall inference for parameters of interest. The Stata tools published here address task (b) and enable analysis of multiple datasets to be performed with similar ease to the analysis of a single dataset. These commands not only implement techniques for inference from multiple imputed datasets but also allow standard manipulations such as transformation and recoding of variables.missing data, multiple imputation, Rubin's rule of combination