If you selected a fractional factorial design in the Designs sub-dialog box, then you can fold the design.
Folding is a way to reduce aliasing. Aliasing, also known as confounding, occurs in fractional factorial designs because the design does not include all the combinations of factor levels. For example, if factor A is confounded with the 3-way interaction BCD, then the estimated effect for A is the sum of the effect of A and the effect of BCD. You cannot determine whether a significant effect is because of A, because of BCD, or because of both terms.
Usually, folding is a part of sequential experimentation. First, you run a small fractional design. After you analyze the design, you can fold the design to add runs that decrease aliasing. To fold an existing design in Minitab, use Modify Design.
When you create a design, you can usually maximize the resolution of the design by using a larger fraction instead of folding the design. However, folding on all factors can create a different alias structure. After you create different designs, you can compare the alias structures to determine whether one best meets your needs.
When a design is folded, a new run is added for each run in the base design, with the sign reversed for the factors you are folding on. All other factors are kept at the same level as in the base design. For more information on folding, go to What is folding?.
When you fold on all factors, Minitab copies the original set of runs and adds them to the design, reversing the signs of all values in the additional runs.
If all the words in the defining relation have an even number of letters, then folding on all factors adds replicates without reducing aliasing. Minitab displays a warning and does not create the design.
When you fold one factor, Minitab copies the original set of runs and adds them the design, reversing the signs of the factor you folded the design on.
If the design is a fractional factorial, then you can select which fraction to use. You can estimate the same terms with any fraction. Usually, you specify a different fraction from the default because one or more combinations of factor levels that are in the principal fraction are impractical to run. For example, the principal fraction always includes the run where all of the factors are at their high setting. The other fractions do not. If setting all of the factors at their high levels is expensive or difficult, you can change the fraction number. For more information on selecting a fraction, go to Factorial and fractional factorial designs.
Select whether Minitab randomizes the run order within each block or stores the design in standard order. Randomization reduces the chances of confounding between the effects of factors in your study with the effects of factors that are not in the study, particularly effects that are time-dependent.
Sometimes, you do not want to randomize the design because factor levels are difficult or expensive to change. Instead, you may want use a split-plot design to minimize the factor level changes. For more information on split-plot designs, go to Split-plot designs in design of experiments.
After the design is in the worksheet, you can change how you view the design and re-randomize the design. To view a design in standard order or random order, use Display Design. To randomize or re-randomize a design, use Modify Design. For more information, go to Overview for Display Design and Modify Design.
To see the number of runs, the alias table, and the other properties of a design without storing the design in a worksheet, deselect Store design in worksheet.
If you want to see the properties of various designs (such as alias tables) before selecting the one design you want to store, deselect this option. If you want to analyze a design, you must store it in the worksheet.