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Outputs (2)

The perils of pre-filling: Lessons from the UK's Annual Survey of Hours and Earning microdata (2023)
Journal Article
Whittard, D., Ritchie, F., Phan, V., Bryson, A., Forth, J., Stokes, L., & Singleton, C. (2023). The perils of pre-filling: Lessons from the UK's Annual Survey of Hours and Earning microdata. Statistical Journal of the IAOS, 39(3), 661-677. https://doi.org/10.3233/SJI-230013

The role of the National Statistical Institution (NSI) is changing, with many now making microdata available to researchers through secure research environments This provides NSIs with an opportunity to benefit from the methodological input from rese... Read More about The perils of pre-filling: Lessons from the UK's Annual Survey of Hours and Earning microdata.

Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities (2023)
Journal Article
Mansouri-Benssassi, E., Rogers, S., Reel, S., Malone, M., Smith, J., Ritchie, F., & Jefferson, E. (2023). Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities. Heliyon, 9(4), Article e15143. https://doi.org/10.1016/j.heliyon.2023.e15143

Introduction: Artificial intelligence (AI) applications in healthcare and medicine have increased in recent years. To enable access to personal data, Trusted Research Environments (TREs) (otherwise known as Safe Havens) provide safe and secure enviro... Read More about Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities.