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Regression analysis under incomplete linkage

Journal Article


Abstract


  • Most probability-based methods used to link records from two distinct data sets

    corresponding to the same target population do not lead to perfect linkage, i.e. there are

    linkage errors in the merged data. Further, the linkage is often incomplete, in the sense

    that many records in the two data sets remain unmatched at the completion of the linkage

    process. This paper introduces methods that correct for the biases due to linkage errors and

    incomplete linkage when carrying out regression analysis using linked data. In particular, it

    focuses on the case where one of the linked data sets is a sample from the target population

    and the other is a register, i.e. it covers the entire target population.

Publication Date


  • 2012

Citation


  • Kim, G. & Chambers, R. L. (2012). Regression analysis under incomplete linkage. Computational Statistics and Data Analysis, 56 (9), 2756-2770.

Scopus Eid


  • 2-s2.0-84859907482

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2044

Number Of Pages


  • 14

Start Page


  • 2756

End Page


  • 2770

Volume


  • 56

Issue


  • 9

Abstract


  • Most probability-based methods used to link records from two distinct data sets

    corresponding to the same target population do not lead to perfect linkage, i.e. there are

    linkage errors in the merged data. Further, the linkage is often incomplete, in the sense

    that many records in the two data sets remain unmatched at the completion of the linkage

    process. This paper introduces methods that correct for the biases due to linkage errors and

    incomplete linkage when carrying out regression analysis using linked data. In particular, it

    focuses on the case where one of the linked data sets is a sample from the target population

    and the other is a register, i.e. it covers the entire target population.

Publication Date


  • 2012

Citation


  • Kim, G. & Chambers, R. L. (2012). Regression analysis under incomplete linkage. Computational Statistics and Data Analysis, 56 (9), 2756-2770.

Scopus Eid


  • 2-s2.0-84859907482

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2044

Number Of Pages


  • 14

Start Page


  • 2756

End Page


  • 2770

Volume


  • 56

Issue


  • 9