The split-plot structure sorts the hard-to-change (HTC) factor(s) into groups of like settings. This reduces the number of times HTC factors are changed during the experiment. There must be at least one HTC factor.
If you have many factors and/or many categoric levels select the Split-Plot Optimal (custom) design on the Factorial tab.
Categoric Factors: How many categoric factors are in the experiment?
Name: (defaults to alphabetically ascending letters) Enter a descriptive name for each factor.
Units: (optional) Enter the units of measure for each factor.
Change: A factor can be set as Easy or Hard to change.
Easy: indicates this factor will be completely randomized and can potentially change from run to run.
Hard: indicates this factor will be changed as little as possible, restricting the randomization.
Type:
Nominal: (default) This type of factor is one that simply uses names or classes to describe the levels, for instance peanut butter types (Creamy, Chunky, SuperChunk).
Ordinal: This type of factor uses numbers that are ordered to show the natural progression, for instance temperature (200, 250, 300 Kelvin), where the baseline is the first level. These will be analyzed using orthogonal polynomial contrasts, which can be broken down into linear, quadratic, cubic, etc. components.
All levels and combinations of levels of categoric factors will be included in the design.
Note
Instead of using ordinal contrasts you may be better off building a response surface design with discrete numeric factors.
Levels: Enter the number of levels (N) for each factor.
L[i]: Specifies the setting to use in the experiment. Specify the exact spelling and punctuation for each of the levels (a.k.a. treatments).
Note
If you change an Ordinal factor level manually, you will also need to appropriately edit the Contrast for that level. The software will keep its default values, which are based on the original spacing of the factor levels. (Honestly, it is easier to just re-build the design with the new factor levels!)