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Multi-collinearity effect in multivariable regression models was excluded by a stepwise approach with each variable included for P < 0.05 and excluded for P > 0.1.
A multicollinearity effect in multivariable regression models was excluded by a stepwise approach, variables being included for p<0.05, excluded for p>0.1.
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Since the equation for computing field-aligned currents explicitly requires the gradient in conductance to be known, the use of statistically averaged models is excluded for case studies.
Some models are excluded or under great tension, while others remain perfectly viable.
Finally, many models are excluded due to poor significance with V85.
Indeed, as Figures 4 and 5 show better accuracy of reproduction when truncated conformer models are excluded.
The forecasting performance is similar when it is used to forecast the three weather variables for fewer locations (results for these more limited models are excluded for sake of brevity).
Patients with missing data for any of the variables in the final models were excluded from the models.
Variables that were not statistically significant in any of the models were excluded from the final multivariable models.
Given that the study is comparative, costs that are common across pharmaceutical care models were excluded [ 34].
Models were excluded if they simply described animals, cell lines, clinical series, cohorts or estimates of individual risk.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com