"To protect the cofidentiality of survey respondents' identities and sensitive attributes, statistical agencies can release data in which cofidential values are replaced with multiple imputations. These are called synthetic data. We propose a two-stage approach to generating synthetic data that...

"The basic concept of multiple imputation is straightforward and easy to understand, but the application to real data imposes many implementation problems. To define useful imputation models for a dataset that consists of categorical and of continuous variables with distributions that are...

"To protect the cofidentiality of survey respondents' identities and sensitive attributes, statistical agencies can release data in which cofidential values are replaced with multiple imputations. These are called synthetic data. We propose a two-stage approach to generating synthetic data that...

"The basic concept of multiple imputation is straightforward and easy to understand, but the application to real data imposes many implementation problems. To define useful imputation models for a dataset that consists of categorical and of continuous variables with distributions that are...