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Once the stepwise selection process completed selecting the variables, the model was run using a standard least squares regression with the effects that were selected by the stepwise process as most active.
Genes were selected for inclusion using a forward stepwise selection process with a significance criterion of 0.01 for entrance into the model.
Variables were removed in a backward stepwise selection process on the basis of a significance level of 0.10 in the univariate analysis.
The stepwise selection process of relevant recommendations ensured that most attention and in-depth analysis is focused to the most promising recommendations.
Because this third group of factors proved less important, it was eliminated during the stepwise selection process.
Therefore the ability of transformed cells to grow in anchorage independent conditions may result from a stepwise selection process, driven by gradual reduction in cell adhesiveness.
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Stepwise selection processes were applied to select the comorbidities of prognostic relevance.
A variable selection was performed using backward and forward stepwise selection processes (the significance level for entry and permanence of a given variable in the model was P < 0.05).
The stepwise-selection process included an alternation between forward selection of a set of significant markers and backward elimination of markers that did not retain significance at the selected threshold after additional markers were placed in the model.
Backward stepwise selection procedure was used.
Classifier development : An L2/ridge-penalized (with the penalty parameter fixed at 2.5, based on optimization of cross-validated model likelihood in previous unrelated projects) logistic regression modeling strategy was employed for feature selection using markers selected by a penalized linear regression forward stepwise feature selection process.
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