Eine Methode, um die Vertraulichkeit von Daten, die in statistischen Ämtern erhobenen werden, zu gewährleisten, ist das Ersetzen vertraulicher Werte durch synthetische Daten, die mittels multipler Imputation generiert werden. Es wird ein zweistufiges Verfahren zur Generierung der synthetischen...

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...

Applications of multiple imputation have long outgrown the traditional context of dealing with item nonresponse in cross-sectional datasets. Nowadays multiple imputation is also applied to impute missing values in hierarchical datasets, address confidentiality concerns, combine data from...

For micro-datasets considered for release as scientific or public use files, statistical agencies have to face the dilemma of guaranteeing the confidentiality of survey respondents on the one hand and offering sufficiently detailed data on the other hand. For that reason a variety of methods to...

Use of microdata is severely hampered in many areas of research. This is in particular true for data from statistical offices. One way to circumvent this problem is to anonymize the data such that both confidentiality is guaranteed and informational content of the data is not to much distorted...

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...