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We would like to kindly thank Stefan Rueckriem, Sara Wüstemann, Clara Luise Buck, Christine Schlitter and Corinna Illgen for their support in data assessment and patient recruitment.
Both internal consistency (meeting typical patterns on age and or sex distribution) and external consistency (comparison of data across censuses from the same country) are vital in data assessment (Moultrie et al. 2013).
UT and WS designed the study and were instrumental in data assessment.
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27 Teachers were not involved in the data assessment.
Patient recruitment started in 2003 and data assessment was completed in 2006.
SMDG participated in collection of data, assessment of dietary factors, and review of the manuscript.
Divergences from the findings of other studies may also be attributable to differences in methods of data assessment: the diagnoses were ascertained from claims data and not made by specially trained personnel in the context of a primary data assessment.
Thus, in addition to quantitative data, assessment of antimicrobial therapy and prophylaxis in individual patients is needed for quality control.
The participants were recruited in August, 2010, and post data assessment was completed in December, 2010.
Although some researches have studied data management in the area of data assessment and data cleaning [14], the relationship between data quality indicators is still a challenging issue.
In addition, methods for data assessment and analysis should aim to minimize confounding variables (see below).
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