Vol. 7 No. 1 (2015) | Journal of Privacy and Confidentiality

This issue was first published at Research Showcase @ CMU (http://repository.cmu.edu/jpc/vol7/iss1/). Research Showcase @ CMU is Carnegie Mellon University’s institutional repository.

DOI: https://doi.org/10.29012/jpc.v7i1

Published: 2015-12-31

In This Issue

Stephen E. Fienberg

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Probabilistic Record Linkage and Deduplication after Indexing, Blocking, and Filtering

Jared S. Murray

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The Effect of Data Swapping on Analyses of American Community Survey Data

Nicolas Kim

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Likelihood Based Finite Sample Inference for Singly Imputed Synthetic Data Under the Multivariate Normal and Multiple Linear Regression Models

Martin Klein, Bimal Sinha

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Designing Incentive Schemes for Privacy-Sensitive Users

Chong Huang, Lalitha Sankar, Anand D. Sarwate

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The Journal of Privacy and Confidentiality is an open-access multi-disciplinary journal whose purpose is to facilitate the coalescence of research methodologies and activities in the areas of privacy, confidentiality, and disclosure limitation. The JPC seeks to publish a wide range of research and review papers, not only from academia, but also from government (especially official statistical agencies) and industry, and to serve as a forum for exchange of views, discussion, and news. For more information, see the About the Journal page.

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In This Issue

Articles

Probabilistic Record Linkage and Deduplication after Indexing, Blocking, and Filtering

The Effect of Data Swapping on Analyses of American Community Survey Data

Likelihood Based Finite Sample Inference for Singly Imputed Synthetic Data Under the Multivariate Normal and Multiple Linear Regression Models

Designing Incentive Schemes for Privacy-Sensitive Users