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LADI: A Latent Discriminant Model for Analyzing Marketing Research Data

LADI: A Latent Discriminant Model for Analyzing Marketing Research Data A general, flexible LAtent DIscriminant model is described. LADI is a model-based clustering procedure, derived from a specific conceptualization in which the discrimination problem is viewed in a latent mixture context. The basic model yields maximum likelihood (ML) estimates of mixing parameters and structural parameters that define the latent clusters in terms of the responses to a set of descriptor variables. Among other features, the model accommodates descriptor variables having different scale properties, allows for the investigation of group structure, provides a statistical test of the number of latent clusters to retain, and allows for constraints to be imposed on the solution. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Marketing Research SAGE

LADI: A Latent Discriminant Model for Analyzing Marketing Research Data

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References (36)

Publisher
SAGE
Copyright
© 1989 American Marketing Association
ISSN
0022-2437
eISSN
1547-7193
DOI
10.1177/002224378902600102
Publisher site
See Article on Publisher Site

Abstract

A general, flexible LAtent DIscriminant model is described. LADI is a model-based clustering procedure, derived from a specific conceptualization in which the discrimination problem is viewed in a latent mixture context. The basic model yields maximum likelihood (ML) estimates of mixing parameters and structural parameters that define the latent clusters in terms of the responses to a set of descriptor variables. Among other features, the model accommodates descriptor variables having different scale properties, allows for the investigation of group structure, provides a statistical test of the number of latent clusters to retain, and allows for constraints to be imposed on the solution.

Journal

Journal of Marketing ResearchSAGE

Published: Feb 1, 1989

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