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Missing samples occurred because of death, discharge from hospitals and samples not drawn.
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We consider nonparametric complex spectral estimation of data sequences with missing samples occurring in arbitrary patterns.
Missing blood samples occurred in 3.8% of the study participants and missed urine and blood samples occurred in 9%.
Missing blood samples occurred because of the inability to puncture the vein.
The first set, low signal degradation due to missing data, are all the tests with 1 sample missing up to 33%% of missing samples.
A transient U elevation from a one-time inhalation exposure could be missed if sampling occurred too long after U exposure, whereas measurements taken at the time of a potential exposure incident may indicate that an exposure to DU has occurred.
However, they are not really suitable for the general missing-data problem where the missing data samples occur in arbitrary patterns.
Missing sampling weights are also a problem.
The missing sample was assumed to correspond to the missing sampling time.
Age, gender and SES were similar in the entire group (N=1207) to those with blood and urine samples (N=1098) which suggests the missing data occurred on a random basis.
Foliar sampling occurred in March 2006.
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