Publication date: 08/13/2020

The Design outline shows the runs for a design that 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 outline provides a number of ways to evaluate the properties of the generated design. Open the Design Evaluation outline to see the following options:

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 in the Technical Details section.

Color Map on Correlations

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

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 in the Evaluate Designs section.

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

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