IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v103i483y2008p989-1001.html
   My bibliography  Save this article

Assessing Identification Risk in Survey Microdata Using Log-Linear Models

Author

Listed:
  • Skinner, Chris
  • Shlomo, Natalie

Abstract

No abstract is available for this item.

Suggested Citation

  • Skinner, Chris & Shlomo, Natalie, 2008. "Assessing Identification Risk in Survey Microdata Using Log-Linear Models," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 989-1001.
    • Handle: RePEc:bes:jnlasa:v:103:i:483:y:2008:p:989-1001
    as

    Download full text from publisher

    File URL: http://pubs.amstat.org/doi/abs/10.1198/016214507000001328
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yue Lin & Ningchuan Xiao, 2023. "Assessing the Impact of Differential Privacy on Population Uniques in Geographically Aggregated Data: The Case of the 2020 U.S. Census," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(5), pages 1-20, October.
    2. Iwona Bąk & Katarzyna Cheba, 2022. "Green Transformation: Applying Statistical Data Analysis to a Systematic Literature Review," Energies, MDPI, vol. 16(1), pages 1-22, December.
    3. Drechsler, Jörg & Reiter, Jerome P., 2011. "An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3232-3243, December.
    4. Cinzia Carota & Maurizio Filippone & Silvia Polettini, 2022. "Assessing Bayesian Semi‐Parametric Log‐Linear Models: An Application to Disclosure Risk Estimation," International Statistical Review, International Statistical Institute, vol. 90(1), pages 165-183, April.
    5. Eurosystem Household Finance and Consumption Network, 2013. "The Eurosystem Household Finance and Consumption Survey - Methodological report," Statistics Paper Series 1, European Central Bank.
    6. Chipperfield James O., 2014. "Disclosure-Protected Inference with Linked Microdata Using a Remote Analysis Server," Journal of Official Statistics, Sciendo, vol. 30(1), pages 123-146, March.
    7. Shlomo, Natalie & Skinner, Chris, 2022. "Measuring risk of re-identification in microdata: state-of-the art and new directions," LSE Research Online Documents on Economics 117168, London School of Economics and Political Science, LSE Library.
    8. James Jackson & Robin Mitra & Brian Francis & Iain Dove, 2022. "Using saturated count models for user‐friendly synthesis of large confidential administrative databases," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1613-1643, October.
    9. Sergio I. Prada & Claudia González-Martínez & Joshua Borton & Johannes Fernandes-Huessy & Craig Holden & Elizabeth Hair & and Tim Mulcahy, 2011. "Avoiding Disclosure of Individually Identifiable Health Information," SAGE Open, , vol. 1(3), pages 21582440114, October.
    10. Prada, Sergio I & Gonzalez, Claudia & Borton, Joshua & Fernandes-Huessy, Johannes & Holden, Craig & Hair, Elizabeth & Mulcahy, Tim, 2011. "Avoiding disclosure of individually identifiable health information: a literature review," MPRA Paper 35463, University Library of Munich, Germany.
    11. Favaro, Stefano & Panero, Francesca & Rigon, Tommaso, 2021. "Bayesian nonparametric disclosure risk assessment," LSE Research Online Documents on Economics 117305, London School of Economics and Political Science, LSE Library.
    12. John M. Abowd & Ian M. Schmutte, 2015. "Economic Analysis and Statistical Disclosure Limitation," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 50(1 (Spring), pages 221-293.
    13. John M. Abowd & Ian M. Schmutte, 2015. "Economic Analysis and Statistical Disclosure Limitation," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(1 (Spring), pages 221-293.
    14. Christine M. O'Keefe & James O. Chipperfield, 2013. "A Summary of Attack Methods and Confidentiality Protection Measures for Fully Automated Remote Analysis Systems," International Statistical Review, International Statistical Institute, vol. 81(3), pages 426-455, December.
    15. Krenzke Tom & Gentleman Jane F. & Li Jianzhu & Moriarity Chris, 2013. "Addressing Disclosure Concerns and Analysis Demands in a Real-Time Online Analytic System," Journal of Official Statistics, Sciendo, vol. 29(1), pages 99-124, March.
    16. Li‐Chun Zhang & Gustav Haraldsen, 2022. "Secure big data collection and processing: Framework, means and opportunities," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1541-1559, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bes:jnlasa:v:103:i:483:y:2008:p:989-1001. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.