As discussed in the section Alias Structure, the alias structure for a factorial design can tell you important information about which effects are confounded and hence cannot be estimated separately from one another. In some cases, you cannot avoid the fact that some potentially active effects are aliased; for example, in resolution 4 designs, some two-factor interactions are aliased with each other and hence cannot be jointly estimated. In this case, you might want a design that has as many two-factor interactions as possible unaliased with any other interaction—that is, as many clear two-factor interactions as possible. This is known as the MaxClear design, and you can use the MAXCLEAR option in the MODEL statement to request it.
To explore how well a given design performs on the MaxClear criterion, you can use the ALIASING option in the EXAMINE statement to examine the alias structure. Clear interactions are those that are displayed by themselves, with no other interactions in their alias chain. Alternatively, the SUMMARY option in the EXAMINE statement displays a summary count of how many interactions there are in total up to a certain order d, how many of those are unaliased with interactions of lower order and are thus in a sense estimable, and how many are unaliased with any interactions of order d or lower and are thus clear.
Obviously, whether an interaction is clear depends on what other effects are considered to be potentially of interest. For a given design, the default order d for considering interaction clarity is the same as the default order d of interactions included in the alias structure. As with the alias structure, you can specify an alternative value of d in the MAXCLEAR option in the MODEL statement or in the SUMMARY option in the EXAMINE statement.