Require a hierarchical model at each step: Minitab can only add or remove terms that maintain hierarchy. Hierarchical Model Choose whether the stepwise procedure must produce a hierarchical model. If your model contains categorical variables, the results are easier to interpret if the categorical terms, at least, are hierarchical.You can remove insignificant terms later. When you choose Backward elimination for a saturated model, Minitab removes a few terms with small effect to obtain a minimal number of error degrees of freedom. Minitab stops when all variables in the model have p-values that are less than or equal to the specified Alpha to remove value. Backward elimination: This method starts with all potential terms in the model and removes the least significant term for each step.Minitab stops when all variables that are not in the model have p-values that are greater than the specified Alpha to enter value. Then, Minitab adds the most significant term for each step. Forward selection: This method starts with an empty model, or includes the terms you specified to include in the initial model or in every model.Minitab stops when all variables that are not in the model have p-values that are greater than the specified Alpha to enter value, and when all variables in the model have p-values that are less than or equal to the specified Alpha to remove value. You can specify terms to include in the initial model or to force into every model. Then, Minitab adds or removes a term for each step. Stepwise: This method starts with an empty model, or includes the terms you specified to include in the initial model or in every model.None: Fit the model with all of the terms that you specify in the Terms sub-dialog box. Specify the method that Minitab uses to fit the model.
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