Design of a Central Composite (Response Surface) Experiment - Generators & Aliases Tab

Design Considerations

Select the Generators & aliases tab of the Design of a Central Composite (Response Surface) Experiment dialog box to access an option to view the correlation matrix for the design matrix, and, thus, to determine the confounding of linear and quadratic main effects, interactions, and blocking variables.

Correlation matrix (main effects and interactions)

Click the Correlation matrix (main effects and interactions) button to produce a spreadsheet that contains the correlations for the effects in the standard second-order model (see Introductory Overview) and the blocking variables (if the current design is blocked). Note that these correlations are based on the current choice of axial distance and the current number of center points (per block) in the design.

Main effects

When computing the correlations, regardless of the chosen factor minima and maxima, the factor values are rescaled so that the respective minimum and maximum values are equal to -1 and +1, respectively, and so that the star-point values are equal to ±Alpha. The quadratic main effects are computed by squaring the (rescaled) factor values.

Interaction effects

To compute the correlations for the interaction effects, STATISTICA creates for each pair of factors a new (added to the design) variable as the product of the values for the two factors.

Block effects

To compute the correlations for the block effects, when computing the correlation matrix, STATISTICA creates noblocks-1 new variables. The values for a blocking variable i for each run are computed as:

bi = -1	if block = 1
1	if block = i+1
0	otherwise