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Improving Privacy for Respondents in Randomized Controlled Trials: A Differential Privacy Approach

In: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and New Findings

Author

Listed:
  • Soumya Mukherjee
  • Aratrika Mustafi
  • Aleksandra Slavković
  • Lars Vilhuber

Abstract

No abstract is available for this item.

Suggested Citation

  • Soumya Mukherjee & Aratrika Mustafi & Aleksandra Slavković & Lars Vilhuber, 2026. "Improving Privacy for Respondents in Randomized Controlled Trials: A Differential Privacy Approach," NBER Chapters, in: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and New Findings, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberch:15020
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    References listed on IDEAS

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    1. Christopher Blattman & Julian C. Jamison & Margaret Sheridan, 2017. "Reducing Crime and Violence: Experimental Evidence from Cognitive Behavioral Therapy in Liberia," American Economic Review, American Economic Association, vol. 107(4), pages 1165-1206, April.
    2. Rachael Meager, 2019. "Understanding the Average Impact of Microcredit Expansions: A Bayesian Hierarchical Analysis of Seven Randomized Experiments," American Economic Journal: Applied Economics, American Economic Association, vol. 11(1), pages 57-91, January.
    3. Nowok, Beata & Raab, Gillian M. & Dibben, Chris, 2016. "synthpop: Bespoke Creation of Synthetic Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i11).
    4. Wasserman, Larry & Zhou, Shuheng, 2010. "A Statistical Framework for Differential Privacy," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 375-389.
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