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For N.Y.U., it helps mitigate the effects of attrition as some of the 15,000 students in the College of Liberal Arts and Science or other four-year undergraduate schools drop out.
The current study also examines possible effects of attrition on estimates of associations between variables.
Oversampling was done to counteract effects of attrition due to e.g. sickness and non-compliance.
Therefore, these results controlled in part for possible selectivity effects of attrition in the sample.
As is common in longitudinal research, this study was the subject to the effects of attrition.
In final consideration of the effects of attrition, it is noted that no intention to treat analysis was carried out.
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Cox regression was used to adjust for the effect of attrition bias.
Fourth, we adjusted for the effect of attrition bias (ICU observation period) by means of Cox regression.
Therefore, further simulation studies are needed to examine the effect of attrition under several different conditions.
Therefore, the effect of attrition dependent on follow-up variables needs to be studied.
Such studies have typically compared the effect of attrition that is completely random to non-random attrition [ 21, 24].
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