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All Outputs (3)

Frameworks, principles, and accreditation: Making data governance work (2022)
Presentation / Conference
Ritchie, F. (2022, November). Frameworks, principles, and accreditation: Making data governance work. Presented at RSS Data Ethics and Governance – origins, progress and priorities, London

Presentation to the Royal Statistical Society Data Ethics Section, covering the origins and development of the Five Safes, the EDRU approach to problems-solving, principles-based regulation, and how these all need to work together to achieve effectiv... Read More about Frameworks, principles, and accreditation: Making data governance work.

Disclosure risks in odds ratios and logistic regression (2022)
Presentation / Conference
Derrick, B., Green, E., Ritchie, F., & White, P. (2022, April). Disclosure risks in odds ratios and logistic regression. Paper presented at Scottish Economic Society Annual Conference 2022: Special session 'Protecting confidentiality in social science research outputs', Glasgow

When publishing statistics from confidential data, there exists a risk that the statistic might inadvertently reveal confidential information. Statistical disclosure control (SDC) aims to reduce that risk to an acceptable level. Most SDC theory is co... Read More about Disclosure risks in odds ratios and logistic regression.

Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation (2022)
Presentation / Conference
Derrick, B., Green, E., Kember, K., Ritchie, F., & White, P. (2022, April). Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation. Paper presented at Scottish Economic Society, Glasgow

Reporting the sample mean, sample standard deviation and sample size could in some cases lead to the unique identification of the underpinning sample. The likelihood of this reveal via direct enumeration of the possible search space decreases with i... Read More about Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies : The case of the mean and standard deviation.