Optimal Split Plot Design - Advanced Tab

Select the Advanced tab of the Optimal split plot design dialog box to access the options described here.

Number of whole plots

This value specifies the number of whole plots in the split plot experiment.

Size of whole plot

This value specifies the size of each whole plot in the split plot experiment.

Number of hard-to-change factors

This value specifies the number of hard-to-change factors for the split plot design. Hard-to-change factors are also referred to as whole-plot factors.

Number of easy-to-change factors

This value specifies the number of easy-to-change factors for the split plot design. Easy-to-change factors are also referred to as subplot factors.

Ratio of whole-plot to error variance

This value specifies the whole-plot to error variance ratio,. This ratio measures the extent to which observations within the same whole plot are correlated. The larger,, the more observations within one whole plot are correlated.

Variance of random error

This value specifies the variance of the random error term, .

Number of tries

This value specifies the number of random starting designs to consider.

Random seed

This value sets the random number generator that is used to create the random starting designs.

Define factor properties

Click Define factor properties button to produce a spreadsheet containing the current factor names, number of levels, type of factor (easy or hard), measurement type of factor (continuous or qualitative), corresponding low and high values for the continuous factors. Type in the desired text and numeric values, and then click the OK button. These values will be used by the D-Optimal split design algorithm.