Estimating Identification Disclosure Risk Using Mixed Membership Models

REFERENCES

• Airoldi , E. M. , Blei , D. M. , Fienberg , S. E. and Xing , E. P. 2008 . “Mixed Membership Stochastic Blockmodels,” . Journal of Machine Learning Research , 9 : 1981 – 2014 .
   PubMed Web of Science ®Google Scholar
• Airoldi , E. M. , Fienberg , S. E. , Joutard , C. and Love , T. M. 2007 . “Discovering Latent Patterns With Hierarchical Bayesian Mixed-Membership Models,” . In Data Mining Patterns: New Methods and Applications , Edited by: Poncelet , P. , Masseglia , F. and Teisseire , M. 240 – 275 . Hershey, PA : IGI Global .
   Google Scholar
• Bertolet , M. 2008 . “To Weight Or Not To Weight? Incorporating Sampling Designs Into Model-Based Analyses,” . Ph.D. dissertation, Carnegie Mellon University
   Google Scholar
• Bethlehem , J. G. , Keller , W. J. and Pannekoek , J. 1990 . “Disclosure Control of Microdata,” . Journal of the American Statistical Association , 85 : 38 – 45 .
   Web of Science ®Google Scholar
• Bishop , Y. , Fienberg , S. and Holland , P. 1975 . Discrete Multivariate Analysis: Theory and Practice , Cambridge , MA : MIT Press (reprinted in 2007 by Springer-Verlag, New York) .
   Google Scholar
• Blei , D. M. and Lafferty , J. D. 2007 . “A Correlated Topic Model of Science,” . The Annals of Applied Statistics , 1 : 17 – 35 .
   Web of Science ®Google Scholar
• Blei , D. M. , Ng , A. and Jordan , M. I. 2003 . “Latent Dirichlet Allocation,” . Journal of Machine Learning Research , 3 : 993 – 1022 .
   Web of Science ®Google Scholar
• Chen , G. and Keller-McNulty , S. 1998 . “Estimation of Identification Disclosure Risk in Microdata,” . Journal of Official Statistics , 14 : 79 – 95 .
   Google Scholar
• Cooil , B. and Varki , S. 2003 . “Using the Conditional Grade-of-Membership Model to Assess Judgment Accuracy,” . Psychometrika , 68 : 453 – 471 .
   Web of Science ®Google Scholar
• Dale , A. and Elliot , M. 2001 . “Proposals for 2001 Samples of Anonymized Records: An Assessment of Disclosure Risk,” . Journal of the Royal Statistical Society, Series A , 164 : 427 – 447 .
   Web of Science ®Google Scholar
• Dobra , A. , Fienberg , S. E. , Rinaldo , A. , Slavkovic , A. B. and Zhou , Y. 2008 . “Algebraic Statistics and Contingency Table Problems: Log-Linear Models, Likelihood Estimation, and Disclosure Limitation,” . In Emerging Applications of Algebraic Geometry , Edited by: Putinar , M. and Sullivant , S. 63 – 88 . New York : Springer .
   Google Scholar
• Drechsler , J. and Reiter , J. P. 2008 . “Accounting for Intruder Uncertainty Due to Sampling When Estimating Identification Disclosure Risks in Partially Synthetic Data,” . In Privacy in Statistical Databases (LNCS 5262) , Edited by: Domingo-Ferrer , J. and Saygin , Y. 227 – 238 . New York : Springer-Verlag .
   Google Scholar
• Duncan , G. T. , Elliott , M. and Salazar-Gonzalez , J. J. 2011 . Statistical Confidentiality: Principles and Practice , Berlin : Springer .
   Google Scholar
• Elamir , E. and Skinner , C. J. 2006 . “Record Level Measures of Disclosure Risk for Survey Microdata,” . Journal of Official Statistics , 22 : 525 – 539 .
   Google Scholar
• Eriksson , N. , Fienberg , S. E. , Rinaldo , A. and Sullivant , S. 2006 . “Polyhedral Conditions for the Nonexistence of the MLE for Hierarchical Log-Linear Models,” . Journal of Symbolic Computation , 41 : 222 – 233 .
   Web of Science ®Google Scholar
• Erosheva , E. 2002 . “Grade of Membership and Latent Structures With Application to Disability Survey Data,” . Ph.D. dissertation, Department of Statistics, Carnegie Mellon University
   Google Scholar
• Erosheva , E. 2005 . “Comparing Latent Structures of the Grade of Membership, Rasch, and Latent Class Models,” . Psychometrika , 70 : 619 – 628 .
   Web of Science ®Google Scholar
• Erosheva , E. , Fienberg , S. and Joutard , C. 2007 . “Describing Disability Through Individual-Level Mixture Models for Multivariate Binary Data,” . The Annals of Applied Statistics , 1 : 502 – 537 .
   Web of Science ®Google Scholar
• Erosheva , E. , Fienberg , S. and Junker , B. 2002 . “Alternative Statistical Models and Representations for Large Sparse Multi-Dimensional Contingency Tables,” . Annales de la faculté des sciences de Toulouse , 11 : 485 – 505 .
   Google Scholar
• Erosheva , E. , Fienberg , S. E. and Lafferty , J. D. 2004 . “Mixed-Membership Models of Scientific Publications,” . Proceedings of the National Academy of Sciences , 101 : 5220 – 5227 .
   PubMed Web of Science ®Google Scholar
• Fellegi , I. P. and Sunter , A. B. 1969 . “A Theory for Record Linkage,” . Journal of the American Statistical Association , 64 : 1183 – 1210 .
   Web of Science ®Google Scholar
• Fienberg , S. E. and Makov , U. E. 1998 . “Confidentiality, Uniqueness, and Disclosure Limitation for Categorical Data,” . Journal of Official Statistics , 14 : 361 – 372 .
   Google Scholar
• Forster , J. and Webb , E. 2007 . “Bayesian Disclosure Risk Assessment: Predicting Small Frequencies in Contingency Tables,” . Journal of the Royal Statistical Society, Series C , 56 : 551 – 570 .
   Web of Science ®Google Scholar
• Gelman , A. , Carlin , J. B. , Stern , H. S. and Rubin , D. B. 2004 . Bayesian Data Analysis , London : Chapman & Hall .
   Google Scholar
• Goodman , L. A. 1974 . “Exploratory Latent Structure Analysis Using Both Identifiable and Unidentifiable Models,” . Biometrika , 61 : 215 – 231 .
   Web of Science ®Google Scholar
• Gormley , C. 2006 . “Statistical Models for Rank Data,” . Ph.D. dissertation, Department of Statistics, University of Dublin, Trinity College
   Google Scholar
• Gormley , I. and Murphy , T. 2008 . “A Mixture of Experts Model for Rank Data With Applications in Election Studies,” . The Annals of Applied Statistics , 2 : 1452 – 1477 .
   Web of Science ®Google Scholar
• Greenberg , B. V. and Zayatz , L. V. 1992 . “Strategies for Measuring Risk in Public Use Microdata Files,” . Statistica Neerlandica , 46 : 33 – 48 .
   Google Scholar
• Haberman , S. J. 1995 . “Review: Statistical Applications Using Fuzzy Sets, by K. Manton, M. Woodbury and H. Tolley,” . Journal of the American Statistical Association , 90 : 1131 – 1133 .
   Google Scholar
• Holland , P. W. and Rosenbaum , P. R. 1986 . “Conditional Association and Unidimensionality in Monotone Latent Variable Models,” . The Annals of Statistics , 14 : 1523 – 1543 .
   Web of Science ®Google Scholar
• Manrique-Vallier , D. 2010 . “Longitudinal Mixed Membership Models With Applications to Survey Disability Data,” . Ph.D. dissertation, Department of Statistics, Carnegie Mellon University
   Google Scholar
• Manrique-Vallier , D. and Fienberg , S. 2008 . “Population Size Estimation Using Individual Level Mixture Models,” . Biometrical Journal , 50 : 1051 – 1063 .
   PubMed Web of Science ®Google Scholar
• Manton , K. G. , Woodbury , M. A. and Tolley , H. D. 1994 . Statistical Applications Using Fuzzy Sets , New York : Wiley .
   Google Scholar
• Pannekoek , J. 1999 . “Statistical Methods for Some Simple Disclosure Limitation Rules,” . Statistica Neerlandica , 53 : 55 – 67 .
   Web of Science ®Google Scholar
• Pritchard , J. K. , Stephens , M. and Donnelly , P. 2000 . “Inference of Population Structure Using Multilocus Genotype Data,” . Genetics , 155 : 945 – 959 .
   PubMed Web of Science ®Google Scholar
• Reiter , J. P. 2005 . “Estimating Identification Risks in Microdata,” . Journal of the American Statistical Association , 100 : 1103 – 1113 .
   Web of Science ®Google Scholar
• Reiter , J. P. and Raghunathan , T. E. 2007 . “The Multiple Adaptations of Multiple Imputation,” . Journal of the American Statistical Association , 102 : 1462 – 1471 .
   Web of Science ®Google Scholar
• Rinaldo , A. 2005 . “Maximum Likelihood Estimates in Large Sparse Contingency Tables,” . Ph.D. dissertation, Department of Statistics, Carnegie Mellon University
   Google Scholar
• Rinott , Y. and Shlomo , N. 2007 . “Variances and Confidence Intervals for Sample Disclosure Risk Measures,” . In Proceedings of the 56th Session of the ISI 22 – 29 .
   Google Scholar
• Rubin , D. B. 1993 . “Discussion: Statistical Disclosure Limitation,” . Journal of Official Statistics , 9 : 462 – 468 .
   Google Scholar
• Ruggles , S. , Alexander , T. , Genadek , K. , Goeken , R. , Schroeder , M. B. and Sobek , M. 2010 . Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database] , Minnesota , MN : University of Minnesota . http://usa.ipums.org
   Google Scholar
• Samuels , S. M. 1998 . “A Bayesian Species-Sampling-Inspired Approach to the Uniques Problem in Microdata,” . Journal of Official Statistics , 14 : 373 – 384 .
   Google Scholar
• Shlomo , N. and Skinner , C. J. 2010 . “Assessing the Protection Provided by Misclassification-Based Disclosure Limitation Methods for Survey Microdata,” . The Annals of Applied Statistics , 4 : 1291 – 1310 .
   Web of Science ®Google Scholar
• Sijtsma , K. and Junker , B. 2006 . “Item Response Theory: Past Performance, Present Developments, and Future Expectations,” . Behaviormetrika , 33 : 75 – 102 .
   Google Scholar
• Skinner , C. and Holmes , D. 1998 . “Estimating the Re-Identification Risk Per Record in Microdata,” . Journal of Official Statistics , 14 : 361 – 372 .
   Google Scholar
• Skinner , C. , Marsh , C. , Openshaw , S. and Wymer , C. 1994 . “Disclosure Control for Census Microdata,” . Journal of Official Statistics , 10 : 31 – 51 .
   Google Scholar
• Skinner , C. J. 1992 . “On Identification Disclosure and Prediction Disclosure for Microdata,” . Statistica Neerlandica , 46 : 21 – 32 .
   Google Scholar
• Skinner , C. J. and Shlomo , N. 2008 . “Assessing Identification Risk in Survey Microdata Using Log-Linear Models,” . Journal of the American Statistical Association , 103 : 989 – 1001 .
   Web of Science ®Google Scholar
• Sweeney , L. 2001 . “Computational Disclosure Control: Theory and Practice,” . Ph.D. dissertation, Massachusetts Institute of Technology
   Google Scholar
• Woodbury , M. , Clive , J. and Garson Jr , A. 1978 . “Mathematical Typology: A Grade of Membership Technique for Obtaining Disease Definition,” . Computers in Biomedical Research , 11 : 277 – 298 .
   PubMedGoogle Scholar
• Yu , M. , Stinchcomb , D. and Cronin , K. 2011 . “Disclosure Risk Assessment for Population-Based Cancer Microdata,” . In American Statistical Association JSM Proceedings of the Survey Research Methods Section 2609 – 2622 .
   Google Scholar