A Iogit vector model and a logit ideal point model are presented for external analysis of paired comparison preference judgments aggregated over a homogeneous group. The logit vector model is hierarchically nested within the logit ideal point model so that statistical tests are avail-able to distinguish between these two models. Generalized least squares estimation procedures are developed to account for heteroscedastic sampling error variances and specification error vari-ances. Two numerical illustrations deal with judgments concerning employee compensation plans and preferences for salt and sugar in the brine of canned green beans. Key words: multidimensional scaling, external analysis of preferences, generalized least squares estimation
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