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Patients with complete and missing data (i.e. missing questionnaires) were compared to examine whether the assumption of data missing in a non-random way could be rejected.
The study was announced on the university hospital intranet, a platform accessible to all employees, and a reminder to send back missing questionnaires was placed one month after the study start.
Women who reported a diagnosis of cardiovascular disease (ICD-9; 390–459) at baseline or who had missing questionnaires, blood, or DNA samples were excluded.
Table of missing questionnaires by timepoint.
Response rates (based on entirely missing questionnaires or unusable questionnaire) at each time point were examined and reasons for missing questionnaires documented.
Another limitation of our study was the number of missing questionnaires.
Similar(29)
In case of missing covariates, due to missing questionnaire data, multiple imputation will be used [ 81].
One participant had missing questionnaire information and could not be classified.
In case of missing questionnaire items, a last observation carried forward analysis (LOCF) was conducted.
One subject was missing questionnaire data, including distance from Khimprom, medical history, and local food consumption.
We excluded 161 women (2%) in the study group who had missing questionnaire data.
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