This paper is in the following e-collection/theme issue:

Statistical Methods for Surveillance and Population Health (188) Clinical Information and Decision Making (1915) Data Science (357) Machine Learning (2076) mHealth for Data Collection and Research (1196) Vaccination and Immunization in the Digital Age (442)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73916, first published .
Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study

Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study

Comparing Multiple Imputation Methods to Address Missing Patient Demographics in Immunization Information Systems: Retrospective Cohort Study

Authors of this article:

Sara Brown1 Author Orcid Image ;   Ousswa Kudia1 Author Orcid Image ;   Kaye Kleine1 Author Orcid Image ;   Bryndan Kidd2 Author Orcid Image ;   Robert Wines2 Author Orcid Image ;   Nathanael Meckes1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Sara Brown   1 , CHES, MPH ;   Ousswa Kudia   1 , MPH ;   Kaye Kleine   1 , MPH, MBA ;   Bryndan Kidd   2 , MS ;   Robert Wines   2 , CPM, CHP, BS ;   Nathanael Meckes   1 , PhD

1 Scientific Services - Analytics, Scientific Technologies Corporation (United States), Phoenix, AZ, United States

2 Immunization Services, West Virginia Department of Health and Human Services, Charleston, WV, United States

Corresponding Author:

  • Sara Brown, CHES, MPH
  • Scientific Services - Analytics
  • Scientific Technologies Corporation (United States)
  • 411 S 1st St
  • Phoenix, AZ 85004
  • United States
  • Phone: 1 480-745-8500
  • Email: sara_brown@stchome.com