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Stratified Differential Privacy in Randomized Response: A Simulation Study

Abstract Number:

926 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Poster 

Participants:

Grace Kim (1)

Institutions:

(1) Wayzata High School, N/A

First Author:

Grace Kim  
Wayzata High School

Presenting Author:

Grace Kim  
Wayzata High School

Abstract Text:

This paper explores the application of stratified differential privacy in randomized response mechanisms to ensure data confidentiality while maintaining analytical utility. Using R simulations, we implement the Warner randomized response technique with stratification, incorporating Laplace and Gaussian noise mechanisms under varying privacy budgets. The study evaluates the bias and variance of the estimated proportions across different strata. Our results highlight the impact of differential privacy parameters on data utility and privacy protection.

Keywords:

Data Privacy|Randomized response technique|Stratified Random Sampling|privacy-preserving| Calibration| Bias

Sponsors:

Korean International Statistical Society

Tracks:

Miscellaneous

Can this be considered for alternate subtype?

Yes

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I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 3, 2025. The registration fee is non-refundable.

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