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This observation matches the prediction of the hypothesis that missing data result from sample-specific dropout rather than locus-specific dropout or true missingness.
Statistical analyses that exclude individuals with missing data result in estimates with less precision compared with the analysis of all individuals, and more importantly, may lead to biased inference.
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Missing data resulting from nonresponse occurred for several variables.
First, there is a fraction of students with missing data resulting in low data quality.
The missing data resulted in a lower n than the actual number of patients.
As with most survey sampling designs, missing data resulting from non-response occurred in several variables.
Missing data resulting from subject attrition is addressed here using two different approaches.
PM causes clean image data to be misdiagnosed as missing data, resulting in damage to the image during restoration.
As with most survey sampling designs, there were missing data (resulting from non-response) for several variables.
Similar to most survey sampling designs, there were missing data (resulting from non-response) for several variables.
A total of 368 officers completed both the pretest and the posttest survey but 52 surveys were unusable due to missing data, resulting in an analytic sample of 316 probation officers (19% of all officers across the state).
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