Propensity score based conditional group swapping for disclosure limitation of strata-defining variables
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Add terms to the query box

Query box

Help
Clear All
i

Propensity score based conditional group swapping for disclosure limitation of strata-defining variables

Filetype[PDF-332.81 KB]


  • English

  • Details:

    • Alternative Title:
      Priv Stat Databases
    • Description:
      In this paper we propose a method for statistical disclosure limitation of categorical variables that we call Conditional Group Swapping. This approach is suitable for design and strata-defining variables, the cross-classification of which leads to the formation of important groups or subpopulations. These groups are considered important because from the point of view of data analysis it is desirable to preserve analytical characteristics within them. In general data swapping can be quite distorting ([12, 18, 15]), especially for the relationships between the variables not only within the subpopulations but for the overall data. To reduce the damage incurred by swapping, we propose to choose the records for swapping using conditional probabilities which depend on the characteristics of the exchanged records. In particular, our approach exploits the results of propensity scores methodology for the computation of swapping probabilities. The experimental results presented in the paper show good utility properties of the method.
    • Pubmed ID:
      32206763
    • Pubmed Central ID:
      PMC7087407
    • Document Type:
    • Collection(s):
    • Main Document Checksum:
    • File Type:

    Supporting Files

    More +

    You May Also Like

    Checkout today's featured content at stacks.cdc.gov