Kamakura, Wagner A.; Srivastava, Rajendra K.
June 1986
Marketing Science;Summer86, Vol. 5 Issue 3, p199
Academic Journal
This paper presents a new ideal point probabilistic choice model. Unlike the model suggested by Cooper and Nakanishi (1983) which attempts to capture choices via a single ideal point, the proposed model, though based on aggregate data, allows for heterogeneity in preferences by estimating a distribution of ideal points. The model accounts for substitutability among choice alternatives and alleviates one of the major sources for the violation of the "Independence from Irrelevant Alternatives" property. It is demonstrated that the final form of the model is a Multinomial Probit, with a covariance matrix that depends on the relative position of the choice alternatives. An empirical application is provided and the resulting parameters arc compared to the distributions of ideal points and attribute weights obtained via LINMAP (at the individual level) and via both the Logit and Probit versions of the model proposed by Cooper and Nakanishi (at the aggregate level).


Related Articles

  • Assessing Fit Quality and Testing for Misspecification in Binary-Dependent Variable Models. Esarey, Justin; Pierce, Andrew // Political Analysis;Oct2012, Vol. 20 Issue 4, p480 

    In this article, we present a technique and critical test statistic for assessing the fit of a binary-dependent variable model (e.g., a logit or probit). We examine how closely a model's predicted probabilities match the observed frequency of events in the data set, and whether these deviations...

  • Computing adjusted risk ratios and risk differences in Stata. Norton, Edward C.; Miller, Morgen M.; Kleinman, Lawrence C. // Stata Journal;2013, Vol. 13 Issue 3, p492 

    In this article, we explain how to calculate adjusted risk ratios and risk differences when reporting results from logit, probit, and related nonlinear models. Building on Stata's margins command, we create a new postestimation command, adjrr, that calculates adjusted risk ratios and adjusted...

  • A MULTIVARIATE POLY MODEL OF BRAND CHOICE AND PURCHASE INCIDENCE. Wagner, Udo; Taudes, Alfred // Marketing Science;Summer86, Vol. 5 Issue 3, p219 

    In this paper we develop an integrated stochastic model of purchase timing and brand selection which incorporates the influence of marketing mix variables, seasonality and trend, and also allows for various individual choice mechanisms. Our approach rests on the assumptions of a zero-order...

  • Models for the probability of concordance in cross-classification tables. Agresti, Alan; Schollenberger, John; Wackerly, Dennis // Quality & Quantity;1987, Vol. 21 Issue 1, p49 

    For cross-classification table having an ordinal response variable, logit and probit models we formulated for the probability that a pair of subjects is concordant. For multidimensional tables, generalized models are given for the probability that the response at one setting of explanatory...

  • Almost Higher Order Stochastic Dominance. Niu, Cuizhen; Guo, Xu // RAIRO -- Operations Research;Jan2014, Vol. 48 Issue 1, p103 

    In this paper, we develop the concept of almost stochastic dominance for higher order preferences and investigate the related properties of this concept.

  • A NEW REPRESENTATION FOR THE CHARACTERISTIC FUNCTION OF STRICTLY GEO-STABLE VECTORS. Klebanov, Lev B.; Mittnik, Stefan // Journal of Applied Probability;Dec2000, Vol. 37 Issue 4, p1137 

    Presents a representation for the characteristic function of the multivariate strictly geo-stable distribution. Definition of the geo-stable model; Risk assessment or estimation; Parametric description and the construction of estimators.

  • Antimode.  // Encyclopedic Reference of Molecular Pharmacology;2004, p92 

    An encyclopedia entry for the term "antimode" is presented, which refers to the cut-off value that separates different functionally defined groups in a bi-modal or multi-modal frequency distribution.

  • A generalized Pearson system useful in reliability analysis. Sankaran, P.G.; Nair, N. Unnikrishnan; Sindhu, T.K. // Statistical Papers;Jan2003, Vol. 44 Issue 1, p125 

    Presents information on a study which analyzed an extended class of Pearson system of distributions in the context of reliability. Extended class and a characterization theorem; Method used to identify an increasing (decreasing) failure rate model in the generalized Pearson system; Lemma; Theorem.

  • On the Connections Between Bridge Distributions, Marginalized Multilevel Models, and Generalized Linear Mixed Models. Molenberghs, Geert; Kenward, Michael G.; Verbeke, Geert; Iddi, Samuel; Efendi, Achmad // International Journal of Statistics & Probability;Nov2013, Vol. 2 Issue 4, p1 

    Generalized linear mixed models (GLMM) are commonly used to analyze hierarchical data. Unlike linear mixed models, they do not automatically provide parametric marginal regression functions, while such functions are needed for population-averaged inferences. This issue has received considerable...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics