Product-concept testing is a popular activity in marketing research. Often the number of new product/service concepts under study far exceeds the time available for any single respondent. Respondents therefore may receive only a subset of the concepts comprising the total design. Researchers are...

A least-squares algorithm for fitting ultrametric and path length or additive trees to two-way, two-mode proximity data is presented. The algorithm utilizes a penalty function to enforce the ultrametric inequality generalized for asymmetric, and generally rectangular (rather than square)...

Models for the representation of proximity data (similarities/dissimilarities) can be categorized into one of three groups of models: continuous spatial models, discrete nonspatial models, and hybrid models (which combine aspects of both spatial and discrete models). Multidimensional scaling...

Ambiguity surrounds any importance measure in cases in which predictor variables are correlated. However, a new measure is proposed that has attractive properties, such as providing individual contributions that are both non-negative and sum to R2. The new measure is compared with four other...

In lieu of Abstract, here is the first paragraph: Jackson provides a clear statement of a basic (and noncontroversial) limitation of all "importance" measures in multiple regression-namely, there is no unambiguous measure of importance in the case of correlated predictor variables. Darlington...

A simple allocation model is developed in which response is assumed to be linear in the logs of the control variables. It is then shown that the optimal allocation of a fixed total resource is proportional to the partial regression weights when the linear-in-logs model is fitted by least...

In this paper we propose two versions of stochastic choice models based on tree structure models — called “tree unfolding models”. These models can be viewed as discrete (tree structure) analogues of a recently proposed class of continuous (spatial) random utility models for paired...

A recently developed probabilistic multidimensional unfolding model for paired comparisons data is described. Unlike the stochastic multidimensional unfolding models previously proposed in the literature, the present model is a moderate utility model. After presenting the model in its most...

An alternating least squares algorithm is developed for con­structing either an ultrametric or an additive tree represen­tation of profile data. The algorithm simultaneously estimates the best fitting tree and optimal variable weights for con­verting the profile data into dissimilarities. An...