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MNI simply replaces each missing data point with the mean of the non-missing values for that marker, which are then discretized to the closer value in {0,1,2}.
Another essential missing data point is the total number of consumers who take a specific product.
However, rather than imputing a single value for a missing data point and treating it as fixed, the multiple imputation framework accounts for uncertainty about the missing data by creating multiple plausible missing values resulting in multiple data sets.
When observations were missing for temperature, sedimentation, POC, PN, PP, chl-a, DOC and SS, mean values of data before and after the missing data point were used to fill data gaps to be able to run the PLS regression.
To be included in the set of predictions tested, a gene had to be the target of an ER QTL whose genotype differed between A/J and C57BL/6J, and also had to have no more than one missing data point in each of the two groups of replication microarrays.
aOne missing data point.
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These are monthly gridded precipitation data based entirely upon rain gauge data interpolated spatially to give a dataset at 0.5° resolution and no missing data points over land.
Given the frequency of gaps present in these data sets, basic concepts have been developed to cope with missing data points.
The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) provides risk-adjusted assessments of surgical programs, traditionally imputing certain missing data points using a single round of multivariable imputation.
b716 missing data points.
cListwise deletion for missing data on vehicle occupants and race rendered 1,343 missing data points.
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