Numeric Selection List for Two-Level Factors

The Half-Normal plot is preferred for selecting the model in two-level factorial designs.

This view lists the statistical information for each estimable term.

There are five status settings

- term will be considered for the model.

- term will not be considered part of the model.

- term aliased with another term and will not be considered for the model.

- indicates that a term was manually forced into the model. It can only be removed manually.

- indicates that a term is required to be in the model by the program. These terms can only be removed if all other grey padlock terms are removed by fitting a mean model.

For factorial designs the default model is the mean intercept only model.

The list of Aliases appears when analyzing a fractional two-level factorial design. Right-click on a term to switch aliasing, this will replace one term with the other.

The standardized effect is the change in the response related to the change in the term’s factors.

The sum of squares for a term is the amount of variation that can be attributed to the term as it changes.

The percent contribution is obtained by summing all the term sum of squares and then taking each individual SS and dividing by the total SS and multiplying by 100. When all terms have the same degrees of freedom, the % contributions can be used to determine which terms are larger contributors than others.

A list of model terms is displayed. Terms can be toggled into or out of the model by double-clicking.

Multiple terms can be selected by clicking on a starting term, holding down the shift key and clicking another term. These two and all terms in between will be selected. Right-click on the selected area to set the statuses for the highlighted terms.

The Auto Select button opens the automatic selection dialog. The algorithms are used to find a subset of the terms marked with an that contains only important terms. Once the automatic selection completes, click the accept button to see what choices the program made.

After the model is chosen, click on the ANOVA tab to continue the analysis and test the selected effects.

A pick list of model terms is displayed. Terms with an next to them have been selected on one of the plots or have large enough effects to be automatically selected by the software. Factorial models are limited to interaction terms and curvature when center points are included in the design.

The selection can be changed by changing the order pull-down and/or double-clicking on a term to toggle an to an and vice versa. Multiple terms can be selected. Click on a starting term then hold down the shift key and click another term. All terms between the two including the ones clicked will be highlighted. Right-click on the highlighted area to set the status for the highlighted terms.

The Auto Selection opens a dialog to instruct the program to find a subset of the terms that only contains important terms. Once the automatic selection completes, click the accept button to see what choices the program made.

Lenth’s ME and SME values are sometimes used to determine which terms should be declared statistically significant. Terms with effects that are greater than the Lenth’s ME value may be significant. Lenth’s values work well for 16-run designs, but tends to under-select terms in smaller designs and over-select terms in larger designs. Use as a starting point, but modify as needed.

After the model is chosen, click on the ANOVA tab to continue the analysis and test the selected effects.