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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
