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Age, gender and enrolment status were used for the imputation model, but not imputed themselves.
The dependent variables were included as predictors in the imputation model but were not imputed.
The single sectors of health care costs were part of the imputation model but were not imputed themselves.
Missing data were not imputed.
The missing calls were not imputed for GWAS.
Variables that were not captured by a state's crash record or hospital databases were not imputed.
Missing data was not imputed for patients who conceived or who neglected to complete a questionnaire.
Missing values were not imputed, and deletion of cases in the models was listwise.
That is, it is not imputed in relation to a goal to achieve.
Missing data were not imputed; all eligible patients were used for analyses.
Missing BMI values were not imputed.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com