Research Paper Volume 16, Issue 4 pp 3056—3067
Multiple imputation of systematically missing data on gait speed in the Swedish National Study on Aging and Care
- 1 Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
- 2 Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, and Stockholm University, Stockholm, Sweden
- 3 Stockholm Gerontology Research Center, Stockholm, Sweden
- 4 Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA
Received: July 14, 2023 Accepted: January 8, 2024 Published: February 14, 2024
https://doi.org/10.18632/aging.205552How to Cite
Copyright: © 2024 Thiesmeier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: There is insufficient investigation of multiple imputation for systematically missing discrete variables in individual participant data meta-analysis (IPDMA) with a small number of included studies. Therefore, this study aims to evaluate the performance of three multiple imputation strategies – fully conditional specification (FCS), multivariate normal (MVN), conditional quantile imputation (CQI) – on systematically missing data on gait speed in the Swedish National Study on Aging and Care (SNAC).
Methods: In total, 1 000 IPDMA were simulated with four prospective cohort studies based on the characteristics of the SNAC. The three multiple imputation strategies were analysed with a two-stage common-effect multivariable logistic model targeting the effect of three levels of gait speed (100% missing in one study) on 5-years mortality with common odds ratios set to OR1 = 0.55 (0.8-1.2 vs ≤0.8 m/s), and OR2 = 0.29 (>1.2 vs ≤0.8 m/s).
Results: The average combined estimate for the mortality odds ratio OR1 (relative bias %) were 0.58 (8.2%), 0.58 (7.5%), and 0.55 (0.7%) for the FCS, MVN, and CQI, respectively. The average combined estimate for the mortality odds ratio OR2 (relative bias %) were 0.30 (2.5%), 0.33 (10.0%), and 0.29 (0.9%) for the FCS, MVN, and CQI respectively.
Conclusions: In our simulations of an IPDMA based on the SNAC where gait speed data was systematically missing in one study, all three imputation methods performed relatively well. The smallest bias was found for the CQI approach.