Privacy-accuracy trade-off optimization in sensitive surveys through regression estimation
Researchers have developed a new regression estimator for sensitive surveys that improves the balance between data privacy and statistical accuracy. The method incorporates non-sensitive auxiliary variables to provide more reliable population estimates while protecting respondent anonymity.
Why it matters
This tool enhances the quality of social and behavioral research by encouraging honest participation in surveys regarding sensitive topics.
Scientific Reports ( 2026 ) Cite this article
We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
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