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Exact(5)
Note that the number of models is low N m = 11.
They predictive power (ability to generate credible predictions) of ln(N t ) and ln(E tT ) models is low based on the adjusted coefficient of determination.
The computational cost of these models is low and they have proven effective in exploring morphodynamic trends and improving our understanding of mesoscale behaviour.
The small samples here mean that the power of our models is low and therefore the inference we can gain from these analyses is limited.
The specificity of all of the screening models is low, as may be expected, but the ASIG algorithm performed better with respect to specificity and reduced the number of referrals for RHC.
Similar(55)
However, the VIFs for our models are low, with an average VIF being around 2. As such, multicollinearity is not a large problem in the models.
Similarly, for the total protein release, the ANN model was superior to the other models although the R 2 values of all models were low (Table 6, lower panel).
The R2 values of the regression models are low.
It should be noted that the explained variance of both linear mixed models was low.
Furthermore, the explanatory power of the multivariate models was low, indicating that there are a number of other factors affecting ANC attendance and perinatal outcomes.
However, the proportion of the variation explained by the models was low, and the proportion of the variance in outcome measures explained by the physical exposures was also low.
Related(20)
predictions is low
systems is low
ones is low
specimens is low
samples is low
methodologies is low
templates is low
choices is low
specimen is low
matrices is low
sample is low
example is low
template is low
later is low
models is evident
models is overdue
models is human
models becomes low
models is inevitable
models is integrationist
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