Description
Randomized response techniques (RRT) are important survey methods when dealing with sensitive topics where there is a significant risk of social desirability response bias unless respondent privacy is ensured. Two important measures to consider, when assessing the quality of a RRT model, are model efficiency and respondent privacy. Unfortunately, they move in opposite directions, so you can’t possibly control both. Statisticians deal with similar problem in reference to confidence level and precision associated with confidence intervals.
Focus of this talk will be on showing how seemingly very efficient looking RRT models might actually be very bad, and on presenting a unified measure of quality of quantitative RRT models which accounts for both model efficiency and respondent privacy.