Published on in Vol 24 , No 9 (2022) :September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33775, first published .
The Data-Adaptive Fellegi-Sunter Model for Probabilistic Record Linkage: Algorithm Development and Validation for Incorporating Missing Data and Field Selection

The Data-Adaptive Fellegi-Sunter Model for Probabilistic Record Linkage: Algorithm Development and Validation for Incorporating Missing Data and Field Selection

The Data-Adaptive Fellegi-Sunter Model for Probabilistic Record Linkage: Algorithm Development and Validation for Incorporating Missing Data and Field Selection

Authors of this article:

Xiaochun Li 1 Author Orcid Image ;   Huiping Xu 1 Author Orcid Image ;   Shaun Grannis 2 Author Orcid Image
Xiaochun Li 1 * , PhD ;   Huiping Xu 1 * , PhD ;   Shaun Grannis 2 , MD

1 Department of Biostatistics and Health Data Science , Indiana University School of Medicine , The Richard M. Fairbanks School of Public Health , Indianapolis , IN , US

2 Data and Analytics , Regenstrief Institute Inc. , Indiana University School of Medicine , Indianapolis , IN , US

*these authors contributed equally

Corresponding Author:

  • Xiaochun Li, PhD
  • Department of Biostatistics and Health Data Science
  • Indiana University School of Medicine
  • The Richard M. Fairbanks School of Public Health
  • HITS, Suite 3000
  • 410 W 10th St.
  • Indianapolis, IN
  • US
  • Phone: 1 317 274 2696
  • Email: xiaochun@iu.edu