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A backward stepwise procedure was applied, to select the variables to be included in the final model.
A backward stepwise procedure was used to select variables retained in each of the final models [24].
Starting with the saturated model, a backward stepwise procedure was used, removing any term with P>0.05.
A backward stepwise procedure was used to remove variables until all variables retained in the final model had p values <0.05.
A backward stepwise procedure was used to remove the variables that were not statistically significant.
A backward stepwise procedure was used to include or exclude explanatory variables in the models.
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Backward stepwise procedures were used.
Backward stepwise procedures were then performed until only variables demonstrating a statistically significant association remained in the final model.
In addition, multiple linear regression analysis with a backward-stepwise procedure was applied to determine the parameters most predictive of the serum leptin concentration.
A backward stepwise procedure (back-step) was used to eliminate variables in the model.
Backward, forward, and stepwise procedures were used and compared to identify the final model with a threshold of 10% for the variables to stay in or enter the model.
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