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  • 1
    Electronic Resource
    Electronic Resource
    A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data (1993)
    Oxford, UK : Blackwell Publishing Ltd
    Decision sciences 24 (1993), S. 0 
    Details
    ISSN: 1540-5915
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Economics
    Notes: A latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group among two alternatives in paired comparison experiments. A modest Monte Carlo analysis of algorithm performance is presented. The proposed model is illustrated with empirical data from a consumer psychology experiment that examines the determinants of perceived consumer risk. The predictive validity of the method is assessed and compared to that of several other procedures. The sensitivity of the method to (randomly) eliminate comparisons, which is important in view of reducing respondent fatigue in the task, is investigated.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1540-5915.1993.tb00508.x
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    A mixture likelihood approach for generalized linear models (1995)
    Springer
    Journal of classification 12 (1995), S. 21-55 
    Details
    ISSN: 1432-1343
    Keywords: Mixture models ; Generalized linear models ; EM algorithm ; Maximum likelihood estimation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A mixture model approach is developed that simultaneously estimates the posterior membership probabilities of observations to a number of unobservable groups or latent classes, and the parameters of a generalized linear model which relates the observations, distributed according to some member of the exponential family, to a set of specified covariates within each Class. We demonstrate how this approach handles many of the existing latent class regression procedures as special cases, as well as a host of other parametric specifications in the exponential family heretofore not mentioned in the latent class literature. As such we generalize the McCullagh and Nelder approach to a latent class framework. The parameters are estimated using maximum likelihood, and an EM algorithm for estimation is provided. A Monte Carlo study of the performance of the algorithm for several distributions is provided, and the model is illustrated in two empirical applications.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01202266
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    Paper (German National Licenses)
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  • 3
    Electronic Resource
    Electronic Resource
    Mixture Model Analysis of Complex Samples (1998)
    Springer
    Journal of classification 15 (1998), S. 225-244 
    Details
    ISSN: 1432-1343
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We investigate the effects of a complex sampling design on the estimation of mixture models. An approximate or pseudo likelihood approach is proposed to obtain consistent estimates of class-specific parameters when the sample arises from such a complex design. The effects of ignoring the sample design are demonstrated empirically in the context of an international value segmentation study in which a multinomial mixture model is applied to identify segment-level value rankings. The analysis reveals that ignoring the sample design results in both an incorrect number of segments as identified by information criteria and biased estimates of segment-level parameters.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s003579900032
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    Paper (German National Licenses)
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  • 4
    Electronic Resource
    Electronic Resource
    Segmentation of Hedonic Consumption: An Application of Latent Class Analysis to Consumer Transaction Databases (1999)
    Springer
    Journal of market-focused management 3 (1999), S. 295-311 
    Details
    ISSN: 1572-8846
    Keywords: Hedonic consumption ; segmentation ; latent class analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Economics
    Notes: Abstract While the broad and growing sector of leisure, culture and entertainment is rapidly adapting to marketing, little is known about segmentation in this field. The sector has customer and transaction databases of very good quality, but usage-based segmentation in this new field poses new problems, as hedonic consumption goods are importantly different from other consumption goods. The type of consumer choice behavior suggested in the literature demands a segmentation of category purchase incidence identified transaction data based on Latent Class Analysis. We illustrate such an approach to a library transaction database. The article concludes with a reflection on the results and suggests further directions for research.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009855123617
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    Paper (German National Licenses)
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  • 5
    Electronic Resource
    Electronic Resource
    Discrete and Continuous Representations of Unobserved Heterogeneity in Choice Modeling (1999)
    Springer
    Marketing letters 10 (1999), S. 219-232 
    Details
    ISSN: 1573-059X
    Keywords: Mixing Distributions ; Multinomial Logit ; Multinomial Probit ; Markov-Chain Monte Carlo ; Simulated Likelihood
    Source: Springer Online Journal Archives 1860-2000
    Topics: Economics
    Notes: Abstract We attempt to provide insights into how heterogeneity has been and can be addressed in choice modeling. In doing so, we deal with three topics: Models of heterogeneity, Methods of estimation and Substantive issues. In describing models we focus on discrete versus continuous representations of heterogeneity. With respect to estimation we contrast Markov Chain Monte Carlo methods and (simulated) likelihood methods. The substantive issues discussed deal with empirical tests of heterogeneity assumptions, the formation of empirical generalisations, the confounding of heterogeneity with state dependence and consideration sets, and normative segmentation.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008054316179
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  • 6
    Electronic Resource
    Electronic Resource
    Latent class metric conjoint analysis (1992)
    Springer
    Marketing letters 3 (1992), S. 273-288 
    Details
    ISSN: 1573-059X
    Keywords: Conjoint Analysis ; Mixtures of Distributions ; Marketing Research ; E-M Algorithm ; Remote Entry Devices
    Source: Springer Online Journal Archives 1860-2000
    Topics: Economics
    Notes: Abstract A latent class methodology for conjoint analysis is proposed, which simultaneously estimates market segment membership and part-worth utilities for each derived market segment using mixtures of multivariate conditional normal distributions. An E-M algorithm to estimate the parameters of these mixtures is briefly discussed. Finally, an application of the methodology to a commercial study (pretest) examining the design of a remote automobile entry device is presented.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00994135
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    Paper (German National Licenses)
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  • 7
    Electronic Resource
    Electronic Resource
    Representing Heterogeneity in Consumer Response Models 1996 Choice Conference Participants (1997)
    Springer
    Marketing letters 8 (1997), S. 335-348 
    Details
    ISSN: 1573-059X
    Keywords: Heterogeneity ; latent structure models ; clusterwise regression ; random coefficients models ; compound distributions
    Source: Springer Online Journal Archives 1860-2000
    Topics: Economics
    Notes: Abstract We define sources of heterogeneity in consumer utility functions relatedto individual differences in response tendencies, drivers of utility, formof the consumer utility function, perceptions of attributes, statedependencies, and stochasticity. A variety of alternative modelingapproaches are reviewed that accommodate subsets of these various sourcesincluding clusterwise regression, latent structure models, compounddistributions, random coefficients models, etc. We conclude by defining anumber of promising research areas in this field.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1007916714911
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    Paper (German National Licenses)
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  • 8
    Electronic Resource
    Electronic Resource
    A spatial interaction model for deriving joint space maps of bundle compositions and market segments from pick-any/J data: An application to new product options (1996)
    Springer
    Marketing letters 7 (1996), S. 131-145 
    Details
    ISSN: 1573-059X
    Source: Springer Online Journal Archives 1860-2000
    Topics: Economics
    Notes: Abstract We propose an approach for deriving joint space maps of bundle compositions and market segments from three-way (e.g., consumers x product options/benefits/features x usage situations/scenarios/time periods) pick-any/J data. The proposed latent structure multidimensional scaling procedure simultaneously extracts market segment and product option positions in a joint space map such that the closer a product option is to a particlar segment, the higher the likelihood of its being chosen by that segment. A segment-level threshold parameter is estimated that spatially delineates the bundle of product options that are predicted to be chosen by each segment. Estimates of the probability of each consumer belonging to the derived segments are simultaneously obtained. Explicit treatment of product and consumer characteristics are allowed via optional model reparameterizations of the product option locations and segment memberships. We illustrate the use of the proposed approach using an actual commercial application involving pick-any/J data gathered by a major hi-tech firm for some 23 advanced technological options for new automobiles.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00434905
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    Paper (German National Licenses)
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  • 9
    Electronic Resource
    Electronic Resource
    Mixtures of (constrained) ultrametric trees (1998)
    Springer
    Psychometrika 63 (1998), S. 419-443 
    Details
    ISSN: 1860-0980
    Keywords: hierarchical clustering ; finite mixtures ; ultrametric trees ; maximum likelihood ; constrained estimation ; latent class analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract This paper presents a new methodology concerned with the estimation of ultrametric trees calibrated on subjects' pairwise proximity judgments of stimuli, capturing subject heterogeneity using a finite mixture formulation. We assume that a number of unobserved classes of subjects exist, each having a different ultrametric tree structure underlying the pairwise proximity judgments. A new likelihood based estimation methodology is presented for those finite mixtures of ultrametric trees, that accommodates ultrametric as well as other external constraints. Various assumptions on the correlation of the error of the dissimilarities are accommodated. The performance of the method to recover known ultrametric tree structures is investigated on synthetic data. An empirical application to published data from Schiffman, Reynolds, and Young (1981) is provided. The ability to deal with external constraints on the tree-topology is demonstrated, and a comparison with an alternative clustering based method is made.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02294863
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    Paper (German National Licenses)
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