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To do so, all two-way interactions were initially included and the model was subsequently reduced using the stepwise procedure implemented in R [31].
We constructed models by using the stepwise procedure without excluding and after excluding bone mineral density.
Regression using the stepwise procedure was performed to isolate the relative contribution of each level in the hierarchical model.
The selection of variables to include in the model was defined using the stepwise procedure with a significant level of p = 0.05 to include variables in the model.
After this multiple logistic regression analyses using the stepwise procedure were performed in order to identify the risk indicators for treatment need.
Prognostic factors were selected using the stepwise procedure, specifying the significant levels for entering an additional explanatory variable into the model as 0.25 and for removing an explanatory variable from the model as 0.15.
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We use the stepwise procedure to select the significant variables.
To investigate associated changes between: child symptoms, on the one hand, and 1) child responses (i.e., child emotional, behavioral, and cognitive responses), 2) parental availability and 3) parent-child interaction on the other, we will use the stepwise procedure in multivariate regression analyses with a maximum of 4 tested predictors.
A final multivariable model was chosen by using the stepwise selection procedure.
Associated variables were entered into logistic regression models using the stepwise selection procedure, one model for each selected complication.
Cox regression models were used to investigate which variables, measured before the first vascular event, predicted a recurrent event using the stepwise backward procedure.
More suggestions(14)
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using the step up procedure
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