Search: Best or Coordinate Exchange or Point Exchange
Optimality: Only the D-optimal criterion is available for split-plot designs.
Edit model: The software will default to a certain type of model, depending on the type of optimal design you are creating. You may customize the model by clicking on the Edit Model button. Adding or subtracting specific terms in a model will alter both the number of runs and specifically which runs are chosen. For more information use the help button on the Edit model button.
Blocks: For each block added to a design, a run is added to the required model points to provide the degrees of freedom to estimate the block effects.
Variance Ratio: The assumed ratio of the whole plots proportion of the total variance to the subplots proportion of total variance. If the assumption is far from the truth, the resulting design and estimates will be less efficient and precise than they could have been. The setting of 1 (proportions are equal) is a robust setting.
Groups: Shows the number of whole-plot groups
Required groups is the number of groups necessary to estimate the coefficients for the hard to change part of the model.
Additional groups are added to so that an ANOVA test for the hard to change part of the model is provided. More groups also improves the precision of the estimates.
Total Groups is the sum of the group boxes.
Runs: Shows the number of points and the purpose for which they are selected.
Required model points is the minimum number of runs to estimate the coefficients of the terms in the designed for model specified under the Edit model button.
Additional model points are extra runs added to the experiment to improve precision estimates or coverage of the factor space.
Total runs is the sum of all the above.
Edit Candidate Points: Click this button if using point exchange and want to limit the type of points the design can consider. More details are provided on the help button found on the Edit Candidate Point dialog.
Options: The more random starts and loops that are allowed the better the design will meet the chosen optimality criterion.