Optimal designs for main effects in linear paired comparison models

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Bayesian optimal designs for discrete choice experiments with partial profiles (2011, background): “Thus far, partial profile designs have only been constructed for main-effects models under the convenient but unrealistic assumption that people have no preference for any of the profiles (Grasshoff et al. 2003, 2004; Grossmann et al. 2006, 2009).”
Optimal paired comparison designs for first-order interactions (2003, methodology): “A design which is constituted by the set of all these pairs is optimal with regard to every invariant design criterion (see Graßhoff et al., 2002). For first-order interaction models we have to consider pairs in which approximately a portion of (I − 1)/I of the attributes shown are distinct and a po”
Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study (2007, background): “Notice that although in recent years the theoretical research work on efficient ED construction for logit models has intensified (see also for more theoretical results) [25,26], it still remains mostly anchored to the basic MNL model, whereas much of the cutting edge empirical research is based on m”