LAUSR

A discrete choice experiment (DCE) is a survey method that gives insight into individual preferences for particular attributes. Traditionally, methods for constructing DCEs focus on identifying the individual effect of each attribute (a main effect). However, an interaction effect between two attributes (a two-factor interaction) better represents real-life trade-offs, and provides us a better understanding of subjects’ competing preferences. In practice it is often unknown which two-factor interactions are significant. To address the uncertainty, we propose the use of minimum aberration blocked designs to construct DCEs. Such designs maximize the number of models with estimable two-factor interactions in a DCE with two-level attributes. We further extend the minimum aberration criteria to DCEs with mixed-level attributes and develop some general theoretical results.