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The multinomial logistic regression showed that the highest level 3-way interaction was significant and a backward stepwise procedure did not eliminate any of the effects.
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Bacterial inactivation, as logarithmic reductions of Enterococcus spp. counts, was modeled through the backward stepwise procedure.
Multivariable models were created by a backward stepwise procedure using Egret for windows.
Starting with the saturated model, a backward stepwise procedure was used, removing any term with P>0.05.
A backward stepwise procedure was applied, to select the variables to be included in the final model.
In all of these GLM and MANOVA analyses, the non-significant covariate terms were eliminated by a backward stepwise procedure.
A backward stepwise procedure was used to select variables retained in each of the final models [24].
© Using backward stepwise procedure.
These covariates were selected using a backward stepwise procedure.
A backward stepwise procedure (back-step) was used to eliminate variables in the model.
A backward stepwise procedure was used to remove the variables that were not statistically significant.
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