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- W2080948596 abstract "Under confidentiality, identifiable data provided for statistical purposes is protected from unauthorized disclosure. Organizations acting as brokers between respondents and data users seek to disseminate useful data products while keeping low the risk of confidentiality disclosure. Recognizing that deidentification of each data record is generally inadequate to protect its confidentiality against attack by a data snooper, agencies restrict the data they release for general use. Typically, these restricted data procedures have involved transformation or masking of the original, collected data through such devices as adding noise, topcoding, data swapping, and recoding. Another approach is to use the original data to determine a statistical model and use it to generate synthetic data. Generically, statistical disclosure limitation is a body of restricted data procedure that transforms data so that release of the transformed data adequately limits disclosure risk. Desirably, statistical analysis of the transformed data leads to inferences similar to that obtained by analysis of the original data. The technical procedures for implementation of disclosure limitation involve a range of mathematical and statistical tools." @default.
- W2080948596 created "2016-06-24" @default.
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- W2080948596 date "2015-01-01" @default.
- W2080948596 modified "2023-09-26" @default.
- W2080948596 title "Confidentiality and Statistical Disclosure Limitations" @default.
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- W2080948596 doi "https://doi.org/10.1016/b978-0-08-097086-8.42113-6" @default.
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