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

Methods and Instruments in Medical Informatics (164) Advanced Data Analytics in eHealth (167) Tools, Programs and Algorithms (320) Secondary Use of Clinical Data for Research and Surveillance (414) Data Science (305) Electronic Health Records (1177) Clinical Information and Decision Making (1641) Big Data (278)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64354, first published .
Imputation and Missing Indicators for Handling Missing Longitudinal Data: Data Simulation Analysis Based on Electronic Health Record Data

Imputation and Missing Indicators for Handling Missing Longitudinal Data: Data Simulation Analysis Based on Electronic Health Record Data

Imputation and Missing Indicators for Handling Missing Longitudinal Data: Data Simulation Analysis Based on Electronic Health Record Data

Authors of this article:

Molly Ehrig1 Author Orcid Image ;   Garrett S Bullock1 Author Orcid Image ;   Xiaoyan Iris Leng1 Author Orcid Image ;   Nicholas M Pajewski1 Author Orcid Image ;   Jaime Lynn Speiser1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Molly Ehrig   1 , MS ;   Garrett S Bullock   1 , PhD, DPT ;   Xiaoyan Iris Leng   1 , MD, PhD ;   Nicholas M Pajewski   1 , PhD ;   Jaime Lynn Speiser   1 , MS, PhD

1 Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston Salem, NC, United States

Corresponding Author:

  • Jaime Lynn Speiser, MS, PhD
  • Department of Biostatistics and Data Science
  • Wake Forest University School of Medicine
  • Medical Center Blvd
  • Winston Salem, NC, 27157
  • United States
  • Phone: 1 3367133469
  • Email: jspeiser@wakehealth.edu