Objectives. To develop an imputation method to produce estimates for suppressed values
within a shared government administrative data set to facilitate accurate data sharing and …

Synthetic data generation is being increasingly used as a privacy preserving approach for
sharing health data. In addition to protecting privacy, it is important to ensure that generated …

There is a significant public demand for rapid data-driven scientific investigations using
aggregated sensitive information. However, many technical challenges and regulatory …

Background Although advanced multiple imputation (MI) methodology has become widely
introduced and increasingly used, few have reported for health surveillance, where missing …

Epidemiologic studies are frequently susceptible to missing information. Omitting
observations with missing variables remains a common strategy in epidemiologic studies …

Statistical agencies have begun to partially synthesize public‐use data for major surveys to
protect the confidentiality of respondents' identities and sensitive attributes by replacing high …

There is a growing expectation that data collected by government-funded studies should be
openly available to ensure research reproducibility, which also increases concerns about …

Statistical agencies that disseminate data to the public are ethically and often legally
required to protect the confidentiality of respondents' identities and sensitive attributes. To …

Large-scale aggregate analyses of anonymized data can yield valuable results and insights
that address public health challenges and provide new avenues for scientific discovery …

Background Health surveys provide a rich array of information but on relatively small
numbers of individuals and evidence suggests that they are becoming less representative …