Publication date: 11/29/2021

The Design outline shows the runs for the custom design. The design is optimal, given the conditions that you have specified. The runs might not appear to be randomized. You can select Run Order options in the Output Options panel before generating your design table.

The Design Evaluation red triangle menu and outlines provide a number of ways to evaluate the properties of the generated custom design.

Use Bayesian Information

Select to use the Bayesian Information matrix in the design diagnostic calculations for designs with If Possible model effects that are not estimable. For more information about the Bayesian Information adjustments see Bayesian D-Optimality.

Note: If all model effects are estimable, the Design Diagnostics are presented for all effects without making the Bayesian Information adjustment. If some terms are inestimable, only the Necessary model terms are presented unless the Use Bayesian Information option is selected.

Power Analysis

Enables you to explore your ability to detect effects of given sizes.

Prediction Variance Profile

Shows the prediction variance over the range of factor settings.

Fraction of Design Space Plot

Shows how much of the model prediction variance lies below (or above) a given value.

Prediction Variance Surface

Shows a surface plot of the prediction variance for any two continuous factors.

Estimation Efficiency

For each parameter, gives the fractional increase in the length of a confidence interval compared to that of an idealized (orthogonal) design, which might not exist. Also gives the relative standard error of the parameters.

Alias Matrix

Gives coefficients that indicate the degree by which the model parameters are biased by effects that are potentially active, but not in the model. You specify the terms representing potentially active effects in the Alias Terms table. See The Alias Matrix.

Color Map on Correlations

Shows the absolute correlation between effects on a plot using an intensity scale.

Note: The default intensity scale is a gray scale. To change the color scale, click the Color Map on Correlations red triangle and select Blue to Gray to Red. For a custom color scale, right-click in the plot and select Color Theme.

Design Diagnostics

Indicates the optimality criterion used to construct the design. Also gives efficiency measures for your design. See Optimality Criterion in Custom Design Options and Optimality Criteria.

Note: The Design Diagnostics outline does not provide the following statistics when the model includes factors with Changes set to Hard or Very Hard or with Estimability set to If Possible: D Efficiency, G Efficiency, A Efficiency.

For more information about the Design Evaluation outline, see Design Evaluation.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).