The inadvertently revealing statistic: A systemic gap in statistical training? (2024)
Journal Article
Derrick, B., Green, E., Ritchie, F., Smith, J., & White, P. (2024). The inadvertently revealing statistic: A systemic gap in statistical training?. Significance, 21(1), 24-27. https://doi.org/10.1093/jrssig/qmae009

While concerns around data privacy are well-known, there's a lack of awareness and training when it comes to the confidentiality risk of published statistics, argue Ben Derrick, Elizabeth Green, Felix Ritchie, Jim Smith, Paul White

SACRO guide to statistical output checking (2023)
Other
Ritchie, F., Green, E., Smith, J., Tilbrook, A., & White, P. (2023). SACRO guide to statistical output checking. [web]

This guide for output SDC is the first report from the SACRO project. It covers, theory of output SDC, including the new statbarns model, practicalities, operational considerations, and FAQs for output checking teams.

Disclosure control issues in complex medical data (2023)
Presentation / Conference
Green, E., Ritchie, F., Smith, J., Western, D., & White, P. (2023, September). Disclosure control issues in complex medical data. Paper presented at UNECE/Eurostat Expert Group on Statisticial Data Confidentiality, Wiesbaden

The covid19 pandemic assisted the acceleration of routine access to medical records for research. In the UK platforms including OpenSafely and NHSDigital, alongside emerging hospital trust based Trusted Research Environments (TREs), demonstrate the u... Read More about Disclosure control issues in complex medical data.

Towards a comprehensive theory and practice of output SDC (2023)
Presentation / Conference
Derrick, B., Green, E., Ritchie, F., & White, P. (2023, September). Towards a comprehensive theory and practice of output SDC. Paper presented at UNECE/Eurostat Expert Group on Statisticial Data Confidentiality, Wiesbaden

In 2000, the statistical disclosure control of outputs (OSDC) was largely limited to models of table protection developed by and intended for national statistical institutes (NSIs), as a particular branch of general SDC theory. However, in this centu... Read More about Towards a comprehensive theory and practice of output SDC.

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.

Estimation of the two-group pilot sample size with a cautionary note on Browne’s formula (2021)
Journal Article
Obodo, S., Toher, D., & White, P. (2021). Estimation of the two-group pilot sample size with a cautionary note on Browne’s formula. Journal of Applied Quantitative Methods, 16(3),

Using data obtained from a pilot study, Browne (1995) proposed a procedure for estimating the sample size needed for a definitive two-arm randomised controlled trial when the minimal important difference is specified. Simulations confirm these findi... Read More about Estimation of the two-group pilot sample size with a cautionary note on Browne’s formula.

Ordinal Logistic Regression as an alternative analysis strategy for the comparison of two independent samples (2021)
Journal Article
Bilski, B., Derrick, B., Toher, D., & White, P. (2021). Ordinal Logistic Regression as an alternative analysis strategy for the comparison of two independent samples. Journal of Applied Quantitative Methods, 16(3),

The two group between subjects design is pervasive with analyses often performed using the Mann Whitney Rank Sum test or using the Welch variant of the t-test. Using simulation it is shown that a dummy variable ordinal logistic regression (OLR) mode... Read More about Ordinal Logistic Regression as an alternative analysis strategy for the comparison of two independent samples.