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Models obtained with stepwise methods varied as we changed their parameters: selection by AIC or BIC and intercept-only baseline model or with forced-in variables.
Any model building method integrated with feature selection must be externally evaluated.
Models were built with backwards stepwise model building.
Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches.
Exact logistic regression was used for multivariable modeling using a forward stepwise model building approach.
Use graphical methods to guide model building.
The first-order conditional estimation method with interaction was used throughout model building.
Rather, both methods aim at predictive model building.
Nonetheless, stepwise model building (see " Methods") indicated that MSP assay classification could be predicted even better using two or more probes.
Backward stepwise regression analysis was undertaken for model building.
A manual forward stepwise approach was then used for model building.
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