How much missing data is too much to impute for longitudinal health indicators? A preliminary guideline for the choice of the extent of missing proportion to impute with multiple imputation by chained equations
Abstract Background The multiple imputation by chained equations (MICE) is a widely used approach for handling missing data. However, its robustness, especially for high missing proportions in health indicators, is under-researched. The study aimed to provide a preliminary guideline for the choice o...
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Main Authors: | K. P. Junaid, Tanvi Kiran, Madhu Gupta, Kamal Kishore, Sujata Siwatch |
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Format: | Article |
Language: | English |
Published: |
BMC
2025-02-01
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Series: | Population Health Metrics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12963-025-00364-2 |
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