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Data quality is high (Schouten et al, 1993b), and data completeness is estimated to be at least 95% (Schouten et al, 1993a).
Data completeness is defined both as "Completeness of observations" and "Cycle slips per observation".
Data completeness is above 96%.
Data completeness is assured in our software version, as all items must be answered before continuation.
The medical staff is not allowed to administer treatment without electronic registration and, therefore, data completeness is 100%.
The data completeness is restricted by the lack of diagnosed cases after workers migrate from Ozyorsk (this date terminates the follow-up period for a worker).
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Data quality factors can be categorized as data completeness (are all the data present?), data reliability (are data recorded in the same way across practices and over time?) and data validity (are the data correct?) [ 14, 15].
Data completeness was also greater for the researcher-completed group for some of the items.
For Hospital B, data completeness was 99.3% (1589/1600 total sections completed over 50 patient records) on account of 11 missing entries.
Data completeness was measured by computing the percentage of items completed for each scale and the instrument.
The between subjects factor ("data completeness") was whether participants did or did not have complete pre-post data on the CORE-OM or the employment questionnaire.
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