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Regression analysis under incomplete linkage

Listed author(s):
  • Kim, Gunky
  • Chambers, Raymond
Registered author(s):

    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.

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    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 56 (2012)
    Issue (Month): 9 ()
    Pages: 2756-2770

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    Handle: RePEc:eee:csdana:v:56:y:2012:i:9:p:2756-2770
    DOI: 10.1016/j.csda.2012.02.026
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    1. Jixian Wang & Peter Donnan, 2002. "Adjusting for missing record linkage in outcome studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(6), pages 873-884.
    2. P. Lahiri & Michael D. Larsen, 2005. "Regression Analysis With Linked Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 222-230, March.
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