Exact(4)
Future research into the subject is going to deal with the combination of this control technique with the design of an observer to estimate the susceptible and infected populations when their true data are not available as it usually occurs in a real situation.
Therefore, in this study if the true data are not known (i.e. if we do not know a priori which are true gene coexpressing pairs) a proper calculation of the sensitivity and specificity is not possible.
Models are a way of representing the complexity of the real world in a more simple and comprehensible form where true data are infeasible or impracticable to obtain.
Although using state-of-the-art methods for imputing missing data provided us with the best estimation of real data, also correcting for differences in study attrition in the intervention and control group, we should acknowledge that having "true" data are preferable in any case.
Similar(56)
Normal forms are an attempt to make sure that true data is not destroyed or false data is not created in the database.
Our experiments show that that the O rate of convergence of the modified data to the true data is propagated to positive times including times after wave breaking.
In this test, four small objects with distinct geometric properties were chosen and their accurate models as reliable true data were generated.
This buffer was a substitute for the true data in scenario 2 (assuming the true data were unknown).
We then repeated these tests on our permuted data, asking how often terms significantly enriched in our true data were enriched in the permuted data sets.
The "true" data were then used in the statistical simulation of model data with the inclusion of both classical and Berkson-like error.
The number of permutations per transcript was increased until the maximum LOD score from the true data was no longer in the top ten of LOD scores from the permutation, or until 1,000,000 permutations were calculated.
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