Stratified Differential Privacy in Randomized Response: A Simulation Study

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 (ε). 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.