When using a Design of Experiments methodology, an alias is when the pattern of pluses (+) and minuses (-) into columns are identical. For example, a main effect is aliased with a two-factor interaction. An example of where this might be seen is in a resolution IV (fractional factorial) experiment. During the analysis, it is impossible to know whether a significant change is due to a main effect or due to an interaction because the columns are identical.
Use: There really isn’t a use for aliasing. Instead, it’s just good to know that when a full factorial design is fractionated, you lose some of the power of the design. One of the things you lose, is the ability to separate the effects of main factors from two-way, or three way (or more) interactions. See also ‘confounding.’
