A practical approach to designing partial-profile choice experiments with two alternatives for estimating main effects and interactions of many two-level attributes

A method is presented which facilitates the practical construction of designs for stated choice experiments in which the choice sets are pairs of partial profiles and where, for a potentially large number of two-level attributes, the main effects and two-factor interactions are to be estimated. Although partly heuristic, the approach has a sound theoretical basis and can be used to generate utility-neutral designs for the multinomial logit model which possess a high statistical efficiency. Applying the method neither requires expert knowledge of design theory nor specialized software and is illustrated with several examples.