Sentence examples for inverse selection from inspiring English sources
They are equal to the households' inverse selection probability4.
Interestingly, after propagation with a large bottleneck, the bacteria retained the smooth O-antigen chain-expressing phenotype, even without a final passage in broth, and no inverse selection against O-antigen chain expression had occurred.
Wang and coauthors 2 show that in many situations, some inverse selection probability-weighted estimators are numerically equivalent to imputation.
In a third step, inverse selection probabilities were calculated to rule out deviations of the net sample of the MoMo-Study from the KiGGS net sample.
Associations were assessed using linear mixed models to account for intraindividual correlation, with inverse selection probability weightings based on case status to allow for greater generalizability.
The I. ricinus SG Kunitz encoding transcripts may adhere to the Red Queen hypothesis, where inverse selection (positive or negative) is a series of one species adapting (the tick) and the other counteradapting (the host).
If the disease is not rare in the target population but the sampling fraction for cases and control is known, a straightforward application of inverse-selection-probability-weighting COCA estimation may be used to recover the correct population inference.
We propose a new algorithm, called inverse weight selection (IWS), that preferentially selects individuals based on the cumulative presence of rare frequency haplotypes to maximize the efficiency of WGS surveys.
It might look something like this: With the clouds layer still selected, invert the selection (select-->inverse or ctrl+shift+i) Press backspace to delete the selection, and then deselect with ctrl+d to leave something like this: Apply filter-->sketch-->Chrome with 0 for detail and 2 for smoothness.
It should be noted that classical design-based inference that consists of weighting the sample observations by the inverse of sample selection probabilities cannot be applied for the prediction of the cluster-specific effects for clusters not in the sample.
