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Abstract:
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This special issue attracted work from a diverse group of people, including statisticians, survey methodologists and computer scientists, all trying to improve the way we handle issues of privacy and confidentiality. We’ll present here an overview of the papers accepted in the issue, and discuss the main themes, challenges and solutions proposed by the authors. On the methodology side, we’ll see that privacy issues continue to be an integral part of data collection and analysis, and that we are still learning and developing best practices in the design and implementation of surveys and other forms of research. On the more statistical side, we notice a sophistication of the machinery used to allow data sharing, with the use of complex non-parametric, semi-parametric and Bayesian models, as well as a focus on inference, in particular in relation with formal privacy guarantees such as differential privacy.
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