Chapter 7: Stated choice experimental design theory: the who, the what and the why
Unlike most survey data where information on both the dependent and independent variables is captured directly from respondents, stated preference data where respondents make decisions based in hypothetical markets, of which stated choice (SC) data is a subset, is unique in that typically only the dependent variable is provided by the respondent. With the exception of covariate information which is often ignored in most analysis, the primary variables of interest, consisting of attributes and their associated levels, are designed in advance and presented to the respondent in the form of competing alternatives in SC studies. However, increasing evidence of both an empirical (for example, Bliemer and Rose, 2011; Louviere et al., 2008) and theoretical nature (for example, Burgess and Street, 2005; Sandor and Wedel, 2001, 2002, 2005) suggests that the allocation of the attribute levels over the experiment may impact upon the model outputs obtained, particularly when small samples are involved. As such, rather than simply randomly assigning the attribute levels shown to respondents over the course of an experiment, experimental design theory has traditionally been applied to allocate the attribute levels to the alternatives in some systematic manner. A review of the literature, however, suggests that little consensus exists as to what specific experimental design theory, or aspects thereof, are appropriate for SC studies.
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