Iterative Stepwise Regression

Iterative stepwise regression adds or removes one independent variable at a time to or from the multiple linear regression equation.

To perform iterative stepwise regression, Predictor:

  1. Calculates the partial F statistic for each independent variable.

  2. Adds the independent variable with the most significant correlation (partial F statistic).

  3. Checks the partial F statistic of the independent variables in the regression equation to see if any became insignificant (have a probability below the minimum) with the addition of the latest independent variable.

  4. Removes the least significant of any insignificant independent variables one at a time.

  5. Repeats step 3 until no insignificant variables remain in the regression equation.

  6. Repeats steps 1 through 5 until one of the following occurs:

    • The model runs out of independent variables.

    • The regression reaches one of the stopping criteria (see the Forward Stepwise Regression for information on how the stopping criteria work).

    • The same independent variable is added and then removed.

The resulting equation always has at least one independent variable.