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Robust regression was used whenever models were unstable.
However, although more detailed analyses were attempted, statistical models were unstable and therefore the results presented are primarily descriptive.
Although these results are similar to those presented, Variance Inflation Factors (VIFs) indicate that these regression models were unstable (see Methods).
Evaluation of interaction terms of AKI and other variables was attempted; however, because of the low number of outcomes, regression models were unstable.
However, these models were unstable; three farms with particularly large model residual values had a great influence on scenario 1 model coefficients (ifNY predictor variable was particularly unstable).
The associations between PM2.5 and all three outcomes were stronger when adjusted for PM2.5 10, but estimates from these models were unstable because of the high correlation between the two pollutants.
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Beyond racial classification, the remainder of the variables tested in our models was unstable, with significance and direction of effect varying by model.
Possible explanations for this inconsistency include that the mutant Cep290 protein in the mouse and cat models is unstable and degraded, folds in such a manner as to affect the structure of the N-terminal region resulting in alteration of binding properties or results in changes in protein localization.
The motion of the electrons in the Rutherford model was unstable because, according to classical mechanics and electromagnetic theory, any charged particle moving on a curved path emits electromagnetic radiation; thus, the electrons would lose energy and spiral into the nucleus.
However, it will be out of control when the model is unstable.
A VIF value greater than 5.0 indicates that the model is unstable; a value between 1.0 and 4.0 indicates that the model is acceptable.
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