Imputing missing laboratory results may return erroneous values because they are not missing at random.

Journal of clinical epidemiology(2023)

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摘要
These data suggest that laboratory data are often not MAR. The direction and extent of differences in missing laboratory test values varies between tests. Overall the abnormality of ordered tests increased as testing likelihood decreased. These results suggest that imputating missing laboratory data may return biased values.
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关键词
Generalized estimating equations,Imputation,Laboratory testing,Missing at random,Missing data,Multiple linear regression
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