Sentence examples for stringent random from inspiring English sources

Exact(1)

The probability of failing to observe a quadruple homozygote as calculated by (5/6) was 25% under the least stringent random chromosome model, and the probabilities of failing to observe a quadruple homozygote for the total number of individuals observed over all markers in the S2G and S2N classes are 2.14×10−8 and 2.26×10−8, respectively.

Similar(59)

The most reliable site of pitch-related activity (x 58, y −30, z 10) was close to the peak identified by the more stringent random-effects analysis.

Here, we report only those analyses that survived stringent Gaussian random field theory cluster correction for multiple comparisons at P<0.05, or at trend level at P<0.1, with an initial voxel-level threshold of P<0.05 uncorrected.

The stochastic inequality is the most stringent inequality between random variables.

To rule out this possibility, we further generated much more stringent but uncorrelated random networks of which a large fraction of edges are overlapped with the biological network.

As stringent controls, 1000 random networks were constructed by preserving the number of direct neighbors for each protein in the original PPI network using the edge switching method [ 22, 24- 26].

By employing a stringent 10-fold random sub-sampling cross-validation to account for this possibility [ 24], our model's PPV with respect to PIA reduced to 0.72 (0.68 to 0.76), but the NPV was maintained at 0.85 (0.83 to 0.88) (+LR and -LR corrected to 3.56 (3.10 to 4.08) and 0.22 (0.18 to 0.26), respectively).

Mr. Armitage, who is associate director of the legal disciplinary board in Michigan, said New Jersey's reputation for stringent discipline comes from its random financial audits and harsh penalties.

For instance, in our textbook analysis study (Sung et al. 2015), we found that in many textbooks, the classic U-tube experiment was used to demonstrate and explain osmosis as governed by stringent scientific law (e.g., random motion of molecules that takes place without external energy input), which is always carried out in a well-defined, lifeless scenario.

Since random-effect modelling has stringent data assumptions (e.g. sufficient number of groups, distributional assumptions of the random effect), robust alternatives such as generalised estimating equations (GEE) or robust variance estimation are often preferable [ 20– 20].

These additional constraints will only make the random null hypothesis more stringent to refute.

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