How Statisticians Should Grapple with Privacy in a Changing Data Landscape

Joshua Snoke, Claire McKay Bowen

ResearchPosted on rand.org Jul 11, 2023Published in: CHANCE, Volume 33, Issue 4, pages 6-13 (2020). doi: 10.1080/09332480.2020.1847947

Suppose you had a data set that contained records of individuals, including demographics such as their age, sex, and race. Suppose also that these data contained additional in-depth personal information, such as financial records, health status, or political opinions. Finally, suppose that you wanted to glean relevant insights from these data using machine learning, causal inference, or survey sampling adjustments. What methods would you use? What best practices would you ensure you followed? Where would you seek information to help guide you in this process?

Read More

Topics

Document Details

  • Copyright: Informa UK Limited
  • Publisher: Taylor & Francis Online
  • Availability: Non-RAND
  • Year: 2020
  • Pages: 8
  • Document Number: EP-70147

This publication is part of the RAND external publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.