Probabilistic, multidimensional unfolding analysis

GENFOLD2: A set of models and algorithms for the general UnFOLDing analysis of preference/dominance data

“…Sch~Snemann and Wang (1972) combine this metric unfolding model with the Bradley-Terry-Luce choice model (Luce 1959), to produce a stochastic unfolding approach that is applicable to paired comparisons data. Zinnes and Griggs (1974) present a probabilistic multidimensional analogue of this model. Davidson (1972Davidson ( , 1973 presents a geometrical analysis for this type of unfolding model.…”

Personality Assessment, Forced-Choice

“…Zinnes and Griggs (1974) developed an IRT model to enable analysis of data arising from forced-choice tests consisting of simple paired comparisons (block size n = 2) of items measuring the same trait (UFC). Item parameters and trait scores for individuals can be estimated using this IRT model.…”

“…Zinnes and Griggs (1974) modified the original deterministic version of Coomb's decision model to make it probabilistic. To this end, they consider "noisy perceptions" of item locations and the person's own ideal point at the time of comparison -three random variables distributed normally around their expected values.…”

Probabilistic Multidimensional Scaling Using a City-Block Metric

“…Ashby 6 Gott, 1988;Ashby 6 Maddox, 1993;Ashby 6 Perrin, 1988;Bijmolt, 1996;Bossuyt, 1990;De Soete, Carroll 6 DeSarbo, 1986;Ennis, Palen, 6 Mullen, 1988;Hefner, 1958;MacKay, 1989;MacKay 6 Zinnes, 1995;Zinnes 6 Griggs, 1974). Exceptions to this pattern of using Euclidean metrics with Gaussian stimuli include Ennis and Ashby (1993) and Ennis 6 Johnson (1993), who computed the moments of city-block distances among dimensionally independent stimuli, and MacKay, Bowen, and Zinnes (1996), who defined the PDF of a city-block distance ratio in a stimulus space of one dimension.…”