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The variables included in the final regression model were selected using forward stepwise and backward stepwise selection procedures, where the significance level for removal from the model was P ≥ 0.01 and the significance level for addition to the model was P < 0.005.
The statistical method Multiple Linear Regression (MLR) implemented in the STATISTICA software was employed in order to select the MDs included in the model by using Forward Stepwise and Backward Stepwise selection procedures.
Backward stepwise selection procedures were used to retain proposed variables in each final model.
Forward and backward stepwise selection procedures were used.
Multiple linear regression was conducted using both forward and backward stepwise selection procedures.
We did not use forward or backward stepwise selection procedures because results may be sensitive to the order of inclusion of the candidate variables (e.g. [ 62, 63]).
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A backward stepwise selection procedure was used to select significant independent variables.
For the latter, variables were selected using a backward stepwise selection procedure, retaining only variables with a p < 0.1 for the final model.
To obtain the final set of variables included in the model we used a backward stepwise selection procedure [54].
Backward stepwise selection procedure was used.
In multivariate analysis, a backward stepwise selection procedure was used.
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