The importance of missing data in estimating BMI trajectories

Gray, L.A. orcid.org/0000-0001-6365-7710 (2024) The importance of missing data in estimating BMI trajectories. Scientific Reports, 14 (1). 17740. ISSN 2045-2322

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Item Type: Article
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© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Keywords: BMI; Growth mixture model; Longitudinal analysis; Missing data; Humans; Body Mass Index; Middle Aged; Diabetes Mellitus, Type 2; Female; Male; Longitudinal Studies; Aged; Overweight; Obesity
Dates:
  • Published: 31 July 2024
  • Published (online): 31 July 2024
  • Accepted: 28 July 2024
  • Submitted: 12 April 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health
Funding Information:
Funder
Grant number
MEDICAL RESEARCH COUNCIL
MR/R01664X/1/MR/S009868/1
Depositing User: Symplectic Sheffield
Date Deposited: 05 Aug 2024 16:05
Last Modified: 05 Aug 2024 16:05
Status: Published
Publisher: Springer Science and Business Media LLC
Refereed: Yes
Identification Number: 10.1038/s41598-024-68764-2
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