An Exponential-Family Multidimensional Scaling Mixture Methodology.

A multidimensional scaling methodology (STUNMIX) for the analysis of subjects preference/choice of stimuli is presented, which integrates previous models into a single framework. Locations of the stimuli and the ideal-points of derived segments of subjects on latent dimensions are estimated simultaneously. The methodology is formulated in the framework of the exponential family of distributions. Possible reparametrizations of stimulus coordinates by stimulus characteristics, as well as of probabilities of segment membership by subject background variables, are permitted. The models are estimated in a maximum likelihood framework.