Exact(4)
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.
This multivariate model was confirmed by using forward stepwise selection.
Factors with P values < 0.05 were then examined further by using forward stepwise multivariate logistic regression analysis.
Analysis of the variables in figs 3-5 by using forward stepwise proportional hazards regression identified 13 independent determinants of HMA.
Similar(56)
Predictive ability of plasma fibrinogen for high GS (over than 28 points) was carried out by binary logistic regression models using forward stepwise selection process.
Analyses were repeated using forward stepwise analysis to assess the consistency of results.
*, Selection using forward stepwise logistic regression.
Multivariable models were constructed using forward stepwise selection methods.
Models were built using forward stepwise regression through the first twelve attributes listed in Table 1, followed by the inclusion of all possible pairwise interactions.
Multivariate survival analysis using forward stepwise Cox proportional hazards regression model was performed including thrombosis and prognostic variables which were identified as significant by univariate analysis.
We used forward stepwise addition using likelihood ratio tests to compare models.
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