Have a personal or library account? Click to login
Statistical Disclosure Limitation in the Presence of Edit Rules Cover

Statistical Disclosure Limitation in the Presence of Edit Rules

Open Access
|Mar 2015

References

  1. Bankier, M., M. Luc, C. Nadeau, and P. Newcombe. 1994. “Imputing Numeric and Qualitative Variables Simultaneously.” In Proceedings of the Section on Survey Research Method of the American Statistical Association, 242-247. Available at: https://www.amstat.org/sections/srms/Proceedings/papers/1994_036.pdf. (accessed February 2015).
  2. Cano, I. and V. Torra. 2011. “Edit Constraints on Microaggregation and Additive Noise.” In Privacy and Security Issues in Data Mining and Machine Learning, edited by 134 Journal of Official Statistics C. Dimitrakakis, A. Gkoulalas-Divanis, A. Mitrokotsa, V.S. Verykios, and Y. Saygin, 1-14. Berlin: Springer.10.1007/978-3-642-19896-0_1
  3. Chen, M.H. and B. Schmeiser. 1993. “Performance of the Gibbs, Hit-and-Run, and Metropolis Samplers.” Journal of Computational and Graphical Statistics 2: 251-272. DOI: http://dx.doi. org/10.2307/1390645.10.2307/1390645
  4. Coutinho, W. and T. de Waal. 2012. Hot Deck Imputation of Numerical Data Under Edit Restrictions. Discussion Paper 2012243, Statistics Netherlands. Available at: http://www.cbs.nl/NR/rdonlyres/6C97F296-EE33-4F26-A813-6432ED530249/0/ 201223x10pub.pdf. (accessed February 2015).
  5. Coutinho, W., T. de Waal, and M. Remmerswaal. 2011. “Imputation of Numerical Data Under Linear Edit Restrictions.” Statistics and Operations Research Transactions 35: 29-62.
  6. Coutinho, W., T. de Waal, and N. Shlomo. 2013. “Calibrated Hot-Deck Donor Imputation Subject to Edit Restrictions.” Journal of Official Statistics 29: 299-321. DOI: http://dx.doi.org/10.2478/jos-2013-0024.10.2478/jos-2013-0024
  7. Cox, L.H., A.F. Karr, and S.K. Kinney. 2011. “Risk-Utility Paradigms for Statistical Disclosure Limitation: How to Think, But Not How to Act.” International Statistical Review 79: 160-183. DOI: http://dx.doi.org/10.1111/j.1751-5823.2011.00140.x. De Waal, T., J. Pannekoek, and S. Scholtus. 2011. Handbook of Statistical Data Editing and Imputation. Hoboken, NJ: Wiley.10.1111/j.1751-5823.2011.00140.x
  8. Defays, D. and P. Nanopoulos. 1993. “Panels of Enterprises and Confidentiality: The Small Aggregates Method.” In Proceedings of the 1992 Symposium on Design and Analysis of Longitudinal Surveys, November 2-4, 1992, 195-204. Ottawa, Ontario, Canada. Available at: http://www.researchgate. net/publication/243784453_Panels_of_enter prises_and_confidentiality_the_small_aggregates_ method. (accessed February 2015).
  9. Domingo-Ferrer, J. and J.M. Mateo-Sanz. 2002. “Practical Data-Oriented Microaggregation for Statistical Disclosure Control.” IEEE Transactions on Knowledge and Data Engineering 14: 189-201. DOI: http://dx.doi.org/10.1109/69.979982.10.1109/69.979982
  10. Domingo-Ferrer, J., F. Sebe, and A. Solanas. 2008. “A Polynomial-Time Approximation to Optimal Multivariate Microaggregation.” Computers and Mathematics with Applications 55: 714-732. DOI: http://dx.doi.org/10.1016/j.camwa.2007.04.034.10.1016/j.camwa.2007.04.034
  11. Domingo-Ferrer, J., J.M. Mateo-Sanz, and V. Torra. 2001. “Comparing SDC Methods for Microdata on the Basis of Information Loss and Disclosure Risk.” In Pre-proceedings of ENKNTTS, 807-826. Available at: http://neon.vb.cbs.nl/casc/NTTSJosep.pdf. (accessed February 2015) Drechsler, J. and J.P. Reiter. 2008. “Accounting for Intruder Uncertainty Due to Sampling When Estimating Identification Disclosure Risks in Partially Synthetic Data.” In Privacy in Statistical Databases, edited by J. Domingo-Ferrer and Y. Saygin, 227-238.
  12. New York: Springer.
  13. Duncan, G.T. and S.L. Stokes. 2004. “Disclosure Risk vs. Data Utility: The R-U Confidentiality Map as Applied to Topcoding.” Chance 17: 16-20. DOI: http://dx.doi.org/10.1080/09332480.2004.10554908.10.1080/09332480.2004.10554908
  14. Fayyoumi, E. and B.J. Oommen. 2010. “A Survey on Statistical Disclosure Control and Microaggregation Techniques for Secure Statistical Databases.” Software: Practice and Experience 40: 1161-1188. DOI: http://dx.doi.org/10.1002/spe.992.10.1002/spe.992
  15. Kim et al.: SDL in the Presence of Edit Rules 135 Fellegi, I.P. and D. Holt. 1976. “A Systematic Approach to Automatic Edit and Imputation.” Journal of the American Statistical Association 71: 17-35. DOI: http://dx.doi.org/10.1080/01621459.1976.10481472.10.1080/01621459.1976.10481472
  16. Geweke, J. 1991. “Efficient Simulation from the Multivariate Normal and Student-T Distributions Subject to Linear Constraints and the Evaluation of Constraint Probabilities.” In Computing Science and Statistics: Proceedings of the 23rd Symposium on the Interface, April 21-24, 1991. 571-578. Seattle, Washington.
  17. Available at: http://citeseerx.ist.psu.edu/viewdoc/download?doi = 10.1.1.27.568& rep = rep1&type = pdf. (accessed February 2015).
  18. Gomatam, S., A.F. Karr, J.P. Reiter, and A.P. Sanil. 2005. “Data Dissemination and Disclosure Limitation in a World Without Microdata: A Risk-Utility Framework for Remote Access Analysis Servers.” Statistical Science 20: 163-177.10.1214/088342305000000043
  19. Groves, R.M. 1989. Survey Errors and Survey Costs. New York: Wiley.10.1002/0471725277
  20. Hedlin, D. 2003. “Score Functions to Reduce Business Survey Editing at the U.K. Office for National Statistics.” Journal of Official Statistics 19: 177-199.
  21. Hundepool, A., J. Domingo-Ferrer, L. Franconi, S. Giessing, E.S. Nordholt, K. Spicer, and P.P. de Wolf. 2012. Statistical Disclosure Control. West Sussex, UK: John Wiley & Sons.10.1002/9781118348239
  22. Ishwaran, H. and L.F. James. 2001. “Gibbs Sampling Methods for Stick-Breaking Priors.” Journal of the American Statistical Association 96: 161-173. DOI: http://dx.doi.org/10.10.1198/016214501750332758
  23. 1198/016214501750332758.
  24. Karr, A.F. 2009. The Role of Transparency in Statistical Disclosure Limitation. Presented at the Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality.
  25. Available at: http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/ 2009/wp. 41.e.pdf. (accessed February 2015).
  26. Kim, H.J., L.H. Cox, A.F. Karr, J.P. Reiter and Q. Wang. 2014a. Simultaneous Edit- Imputation for Contineous Microdata. Technical Report 189, National Institute of Statistical Sciences, Research Triangle Park, NC. Available at: https://www.niss.org/ sites/default/files/tr189_updated.pdf (accessed February 2015).10.2139/ssrn.2698601
  27. Kim, H.J., J.P. Reiter, Q. Wang, L.H. Cox, and A.F. Karr. 2014b. “Multiple Imputation of Missing or Faulty Values Under Linear Constraints.” Journal of Business & Economic Statistics 32: 375-386. DOI: http://dx.doi.org/10.1080/07350015.2014.885435.10.1080/07350015.2014.885435
  28. Kim, J.J. 1986. “A Method for Limiting Disclosure in Microdata Based on Random Noise and Transformation.” In Proceedings of the Section on Survey Research Method of the American Statistical Association, 370-374. Available at: https://www.amstat.org/ sections/srms/Proceedings/papers/1986_069.pdf. (accessed February 2015).
  29. Kullback, S. and R.A. Leibler. 1951. “On Information and Sufficiency.” The Annals of Mathematical Statistics 22: 79-86.10.1214/aoms/1177729694
  30. Lavine, M. and M. West. 1992. “A Bayesian Method for Classification and Discrimination.” Canadian Journal of Statistics 20: 451-461. DOI: http://dx.doi.org/ 10.2307/3315614.10.2307/3315614
  31. Little, R.J.A. 1993. “Statistical Analysis of Masked Data.” Journal of Official Statistics 9: 407-426.
  32. Meng, X.L. and A.M. Zaslavsky. 2002. “Single Observation Unbiased Priors.” The Annals of Statistics 30: 1345-1375.10.1214/aos/1035844979
  33. 136 Journal of Official Statistics Moore, R.A. 1996. Controlled Data-Swapping Techniques for Masking Use Microdata Sets. Research Report RR96/04, Statistical Research Division, U.S. Bureau of the Census, Washington, DC. Available at: https://www.census.gov/srd/papers/pdf/ rr96-4.pdf. (accessed February 2015).
  34. Oganian, A. and A.F. Karr. 2006. “Combinations of SDC Methods for Microdata Protection.” In Privacy in Statistical Databases 2006, Lecture Notes in Computer Science, edited by J. Domingo-Ferrer and L. Franconi. 102-113. Berlin: Springer.10.1007/11930242_10
  35. O'Malley, A.J. and A.M. Zaslavsky. 2008. “Domain-Level Covariance Analysis for Multilevel Survey Data With Structured Nonresponse.” Journal of the American Statistical Association 103: 1405-1418. DOI: http://dx.doi.org/10.1198/ 016214508000000724.10.1198/016214508000000724
  36. Petrin, A. and T.K. White. 2011. “The Impact of Plant-Level Resource Reallocations and Technical Progress on U.S. Macroeconomic Growth.” Review of Economic Dynamics 14: 3-26. DOI: http://dx.doi.org/10.1016/j.red.2010.09.004.10.1016/j.red.2010.09.004
  37. Raghunathan, T.E., J.M. Lepkowski, J. van Hoewyk, and P. Solenberger. 2001. “A Multivariate Technique for Multiply Imputing Missing Values Using a Sequence of Regression Models.” Survey Methodology 27: 85-95.
  38. Reiter, J.P. 2003. “Inference for Partially Synthetic, Public Use Microdata Sets.” Survey Methodology 29: 181-188.
  39. Reiter, J.P. 2004. “Simultaneous Use of Multiple Imputation for Missing Data and Disclosure Limitation.” Survey Methodology 30: 235-242.
  40. Reiter, J.P. 2005. “Estimating Risks of Identification Disclosure in Microdata.” Journal of the American Statistical Association 100: 1103-1112. DOI: http://dx.doi.org/10.1198/ 016214505000000619.10.1198/016214505000000619
  41. Reiter, J.P. and R. Mitra. 2009. “Estimating Risks of Identification Disclosure in Partially Synthetic Data.” Journal of Privacy and Confidentiality 1: 99-110.10.29012/jpc.v1i1.567
  42. Rubin, D.B. 1993. “Statistical Disclosure Limitation.” Journal of Official Statistics 9: 461-468.
  43. Sethuraman, J. 1994. “A Constructive Definition of Dirichlet Priors.” Statistica Sinica 4: 639-650.
  44. Shlomo, N. and T. de Waal. 2005. Preserving Edits When Perturbing Microdata for Statistical Disclosure Control. S3RI Methodology Working Paper M05/12, Southampton Statistical Sciences Research Institute. Available at: http://eprints.soton.
  45. ac.uk/14725/1/14725-01.pdf. (accessed February 2015).10.5465/ambpp.2015.14725abstract
  46. Shlomo, N. and T. de Waal. 2008. “Protection of Micro-Data Subject to Edit Constraints Against Statistical Disclosure.” Journal of Official Statistics 24: 229-253.
  47. Solanas, A. and A. Martnez-Balleste. 2006. “V-MDAV: A Multivariate Microaggregation With Variable Group Size.” In Proceedings of the 17th IASC Symposium on Computational Statistics, August 28-September 1, 2006. 917-925. Rome, Italy. Available at: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.332.1680& rep=rep1&type=pdf. (accessed February 2015).
  48. Sullivan, G. and W.A. Fuller. 1989. “The Use of Measurement Error to Avoid Disclosure.” In Proceedings of the Section on Survey Research Method of the American Statistical Association, 802-807. Available at: https://www.amstat.org/sections/srms/Proceedings/ papers/1989_148.pdf. (accessed February 2015).
  49. Kim et al.: SDL in the Presence of Edit Rules 137 Tempelman, C. 2007. Imputation of Restricted Data. Ph. D. dissertation, University of Groningen. Available at: http://dissertations.ub.rug.nl/faculties/eco/2007/d.c.g.
  50. tempelman. (accessed February 2015).
  51. Tendick, P. 1991. “Optimal Noise Addition for Preserving Confidentiality in Multivariate Data.” Journal of Statistical Planning and Inference 27: 341-353. DOI: http://dx.doi.10.1016/0378-3758(91)90047-I
  52. org/10.1016/0378-3758(91)90047-I.
  53. Thompson, K.J., K. Sausman, M. Walkup, S. Dahl, C. King, and S.A. Adeshiyan. 2001.
  54. Developing Ratio Edits and Imputation Parameters for the Services Sector Censuses Plain Vanilla Ratio Edit Module Test. Economic Statistical Methods Report ESM-0101, U.S. Bureau of the Census, Washington, DC.
  55. Torra, V. 2008. “Constrained Microaggregation.” Transactions on Data Privacy 1: 86-104.
  56. Van Buuren, S. and K. Oudshoorn. 1999. Flexible Multivariate Imputation by MICE.
  57. Technical Report PG/VGZ/99.054, TNO Prevention and Health, Leiden, Netherlands.
  58. Available at: http://www. stefvanbuuren.nl/publications/Flexible%20multivariate% 20-%20TNO99054%201999.pdf. (accessed February 2015) Willenborg, L. and T. de Waal. 2001. Elements of Statistical Disclosure Control.
  59. New York: Springer-Verlag.
  60. Winkler, W.E. and L.R. Draper. 1996. Application of the SPEER Edit System.
  61. Research Report RR96/02, Statistical Research Division, U.S. Bureau of the Census, Washington, DC. Available at: https://www.census.gov/srd/papers/pdf/rr96-2.pdf.
  62. (accessed February 2015).
  63. Woo, M.J., J.P. Reiter, A. Oganian, and A.F. Karr. 2009. “Global Measures of Data Utility for Microdata Masked for Disclosure Limitation.” Journal of Privacy and Confidentiality 1: 111-124.10.29012/jpc.v1i1.568
Language: English
Page range: 121 - 138
Submitted on: Oct 1, 2013
|
Accepted on: Sep 1, 2014
|
Published on: Mar 1, 2015
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Hang J. Kim, Alan F. Karr, Jerome P. Reiter, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.