This paper compares four design strategies for choice-based experiments: catalog-based designs for full-profile experiments, recipe-based designs for partial profile experiments, computer optimized designs using SAS OPTEX software; and randomized designs using CBC software. The authors (Chrzan and Orme) compare these strategies in terms of design efficiency and their ability to capture particular effects (main, cross- and alternative-specific effects, and interactions).
CBC software is found to create optimal or near-optimal designs in all cases, with the exception of designs in which many more first-order interactions are modeled relative to main effects. SAS OPTEX software is shown to provide optimal or near-optimal designs in all cases for which it is applicable. For main-effect only designs, minimal level overlap strategies are favored. For higher-order effects, level overlap within tasks is desirable. A special case is demonstrated in which carefully chosen prohibitions between attribute levels can actually improve the efficiency of designs. D-efficiency computation using CBC and SPSS software is detailed in the appendix. This paper was voted "Most Valuable Presentation" at the 2000 Sawtooth Software Conference.
