Disclosure control and data dissemination
Results
All (8)
All (8) ((8 results))
- Stats in brief: 89-20-00082021001Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-29
- Stats in brief: 89-20-00082021002Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021003Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021004Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-27
- Stats in brief: 89-20-00082021005Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021006Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-27
- Articles and reports: 11-522-X201700014735Description:
Microdata dissemination normally requires data reduction and modification methods be applied, and the degree to which these methods are applied depend on the control methods that will be required to access and use the data. An approach that is in some circumstances more suitable for accessing data for statistical purposes is secure computation, which involves computing analytic functions on encrypted data without the need to decrypt the underlying source data to run a statistical analysis. This approach also allows multiple sites to contribute data while providing strong privacy guarantees. This way the data can be pooled and contributors can compute analytic functions without either party knowing their inputs. We explain how secure computation can be applied in practical contexts, with some theoretical results and real healthcare examples.
Release date: 2016-03-24 - Articles and reports: 11-522-X20010016300Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The Australian Bureau of Statistics (ABS) produces many statistics that help the government and the wider community make more informed decisions. However, if these decisions are to be truly informed, it is essential that the users are able to understand the limitations of the statistics and how to use the data in an appropriate context. As a result, the ABS has initiated a project entitled Qualifying Quality, which focuses on two key directions: presentation and education. Presentation provides people with information about the quality of the data in order to help them answer the question "Are the data fit for the purpose?"; while education assists those people in appreciating the importance of information on quality and knowing how to use such information. In addressing these two issues, the project also aims to develop and identify processes and technical systems that will support and encourage the appropriate use of data.
This paper provides an overview of the presentation and education initiatives which have arisen from this project. The paper then explores the different methods of presentation, the systems that support them, and how the education strategies interact with each other. In particular, the paper comments on the importance of supporting education strategies with well developed systems and appropriate presentation methods.
Release date: 2002-09-12
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Analysis (8)
Analysis (8) ((8 results))
- Stats in brief: 89-20-00082021001Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-29
- Stats in brief: 89-20-00082021002Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021003Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021004Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-27
- Stats in brief: 89-20-00082021005Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021006Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-27
- Articles and reports: 11-522-X201700014735Description:
Microdata dissemination normally requires data reduction and modification methods be applied, and the degree to which these methods are applied depend on the control methods that will be required to access and use the data. An approach that is in some circumstances more suitable for accessing data for statistical purposes is secure computation, which involves computing analytic functions on encrypted data without the need to decrypt the underlying source data to run a statistical analysis. This approach also allows multiple sites to contribute data while providing strong privacy guarantees. This way the data can be pooled and contributors can compute analytic functions without either party knowing their inputs. We explain how secure computation can be applied in practical contexts, with some theoretical results and real healthcare examples.
Release date: 2016-03-24 - Articles and reports: 11-522-X20010016300Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The Australian Bureau of Statistics (ABS) produces many statistics that help the government and the wider community make more informed decisions. However, if these decisions are to be truly informed, it is essential that the users are able to understand the limitations of the statistics and how to use the data in an appropriate context. As a result, the ABS has initiated a project entitled Qualifying Quality, which focuses on two key directions: presentation and education. Presentation provides people with information about the quality of the data in order to help them answer the question "Are the data fit for the purpose?"; while education assists those people in appreciating the importance of information on quality and knowing how to use such information. In addressing these two issues, the project also aims to develop and identify processes and technical systems that will support and encourage the appropriate use of data.
This paper provides an overview of the presentation and education initiatives which have arisen from this project. The paper then explores the different methods of presentation, the systems that support them, and how the education strategies interact with each other. In particular, the paper comments on the importance of supporting education strategies with well developed systems and appropriate presentation methods.
Release date: 2002-09-12
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